A method of grasping and/or placing multiple objects by a gripper of a mobile robot. The multi-grasp method includes determining one or more candidate groups of objects to grasp by the suction-based gripper of the mobile robot, each of the one or more candidate groups of objects including a plurality of objects, determining a grasp quality score for each of the one or more candidate groups of objects, and grasping, by the suction-based gripper of the mobile robot, all objects in a candidate group of objects based, at least in part, on the grasp quality score. The multi-place method includes determining an allowed width associated with the conveyor, selecting a multi-place technique based, at least in part, on the allowed width and a dimension of the multiple grasped objects, and controlling the mobile robot to place the multiple grasped objects on the conveyor based on the selected multi-place technique.
An electric motor for a mobile robot includes a rotor including a rotor hub and a magnetic structure coupled to the rotor hub. The magnetic structure is configured to provide an active surface. The active surface includes a circular array of radial magnetic poles of alternating polarity. The electric motor further includes a stator comprising a non-segmented structure including a set of teeth and a set of slots arranged between individual teeth of the set of teeth, wherein each tooth of the set of teeth has a surface over which a respective coil is configured to be placed within adjacent slots of the tooth. The electric motor further includes a set of coils arranged within the set of slots of the stator, and a printed circuit board electrically coupled to each of the coils in the set of coils.
H02K 1/2783 - Surface mounted magnetsInset magnets with magnets arranged in Halbach arrays
H02K 1/2792 - Surface mounted magnetsInset magnets with magnets arranged in Halbach arrays
H02K 11/33 - Drive circuits, e.g. power electronics
H02K 21/16 - Synchronous motors having permanent magnetsSynchronous generators having permanent magnets with stationary armatures and rotating magnets with magnets rotating within the armatures having annular armature cores with salient poles
H02K 21/22 - Synchronous motors having permanent magnetsSynchronous generators having permanent magnets with stationary armatures and rotating magnets with magnets rotating around the armatures, e.g. flywheel magnetos
H02K 3/52 - Fastening salient pole windings or connections thereto
A stator for an electric motor is provided. The stator include a non-segmented metal support comprising a set of straight teeth and a set of slots between the set of straight teeth, a set of coils, and a fixing component configured to secure the set of coils into the set of slots. Each coil in the set of coils is formed from square or rectangular copper wire into a single layer with fifteen or fewer turns, and arranged on a corresponding straight tooth of the non-segmented metal support such that the coil occupies corresponding slots in the set of slots on either side of the straight tooth.
A magnetizer for magnetizing a ring magnet is provided. The magnetizer includes a set of capacitors and a core including a set of teeth, a set of coils arranged on the set of teeth, a set of conductors, each conductor in the set of conductors being electrically coupled to a coil in the set of coils, and a set of switches electrically coupled between a conductor in the set of conductors and one or more capacitors in the set of capacitors, wherein each switch in the set of switches is configured to be controlled independently of other switches in the set of switches.
H01F 13/00 - Apparatus or processes for magnetising or demagnetising
H02K 15/03 - Processes or apparatus specially adapted for manufacturing, assembling, maintaining or repairing of dynamo-electric machines of stator or rotor bodies having permanent magnets
Method and apparatus for grasping an empty pallet using a mobile robotic device are provided. Sensor data captured by at least one sensor is used to identify an empty pallet. Based on at least one characteristic of the empty pallet and at least one capability of a mobile robotic device, it is determined whether to grasp the empty pallet using an end effector of the mobile robotic device. The empty pallet is grasped using the end effector of the robotic device. In response to determining, based on image capture data corresponding to an initial position in which the empty pallet is placed on a cart coupled to the mobile robotic device, that the initial position is different from a target position, the empty pallet is moved from the initial position to the target position using the end effector.
B25J 5/00 - Manipulators mounted on wheels or on carriages
B66F 9/06 - Devices for lifting or lowering bulky or heavy goods for loading or unloading purposes movable, with their loads, on wheels or the like, e.g. fork-lift trucks
Method and apparatus for grasping an empty pallet using a mobile robotic device are provided. Sensor data captured by at least one sensor is used to identify an empty pallet. Based on at least one characteristic of the empty pallet and at least one capability of a mobile robotic device, it is determined whether to grasp the empty pallet using an end effector of the mobile robotic device. The empty pallet is grasped using the end effector of the robotic device. In response to determining, based on image capture data corresponding to an initial position in which the empty pallet is placed on a cart coupled to the mobile robotic device, that the initial position is different from a target position, the empty pallet is moved from the initial position to the target position using the end effector.
Methods and apparatus for controlling a robot are provided. The method includes receiving a kinematic trajectory for a robot, wherein the kinematic trajectory is based, at least in part, on one or more features extracted from video data, the video data including one or more bipeds performing a task by interacting with one or more objects, the one or more features including a first feature corresponding to a biped and second feature corresponding to an object, and determining a control policy for the robot based, at least in part, on the kinematic trajectory.
An electric motor for a mobile robot includes a rotor including a rotor hub and a magnetic structure coupled to the rotor hub. The magnetic structure is configured to provide an active surface. The active surface includes a circular array of radial magnetic poles of alternating polarity. The electric motor further includes a stator comprising a non-segmented structure including a set of teeth and a set of slots arranged between individual teeth of the set of teeth, wherein each tooth of the set of teeth has a surface over which a respective coil is configured to be placed within adjacent slots of the tooth. The electric motor further includes a set of coils arranged within the set of slots of the stator, and a printed circuit board electrically coupled to each of the coils in the set of coils.
H02K 21/16 - Synchronous motors having permanent magnetsSynchronous generators having permanent magnets with stationary armatures and rotating magnets with magnets rotating within the armatures having annular armature cores with salient poles
A stator for an electric motor is provided. The stator include a non-segmented metal support comprising a set of straight teeth and a set of slots between the set of straight teeth, a set of coils, and a fixing component configured to secure the set of coils into the set of slots. Each coil in the set of coils is formed from square or rectangular copper wire into a single layer with fifteen or fewer turns, and arranged on a corresponding straight tooth of the non-segmented metal support such that the coil occupies corresponding slots in the set of slots on either side of the straight tooth.
Systems and methods are described for detecting changes at a location based on image data by a mobile robot. A system can instruct navigation of the mobile robot to a location. For example, the system can instruct navigation to the location as part of an inspection mission. The system can obtain input identifying a change detection. Based on the change detection and obtained image data associated with the location, the system can perform the change detection and detect a change associated with the location. For example, the system can perform the change detection based on one or more regions of interest of the obtained image data. Based on the detected change and a reference model, the system can determine presence of an anomaly condition in the obtained image data.
G05D 1/689 - Pointing payloads towards fixed or moving targets
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
G05D 105/80 - Specific applications of the controlled vehicles for information gathering, e.g. for academic research
Methods and apparatus for controlling a robot are provided. The method includes receiving a kinematic trajectory for a robot, wherein the kinematic trajectory is based, at least in part, on one or more features extracted from video data, the video data including one or more bipeds performing a task by interacting with one or more objects, the one or more features including a first feature corresponding to a biped and second feature corresponding to an object, and determining a control policy for the robot based, at least in part, on the kinematic trajectory.
A control system for a mobile robot is provided. The control system includes a first controller configured to control movement of the mobile robot to provide dynamic balancing of the mobile robot, a second controller configured to control movement of a first portion of the mobile robot, and a first dynamics module configured to coordinate operation of the first controller and the second controller.
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
B62D 57/036 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members screw type, e.g. Archimedian screw
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
13.
SYSTEMS AND METHODS FOR CALIBRATING ROBOT ACTUATORS USING IMAGE DATA
Method and apparatus for calibrating actuators of a robot using image data are provided. Image data is received from at least one sensor when a robot is in a pose, where a joint of the robot represented in the image data has an expected joint position when the robot is in the pose. Based on the image data, an actual joint position of the joint when the robot is in the pose is determined. When it is determined that the actual joint position of the joint is different from the expected joint position of the first joint, an encoder of an actuator associated with the joint is configured based, at least in part, on the actual joint position of the joint.
Method and apparatus for calibrating actuators of a robot using image data are provided. Image data is received from at least one sensor when a robot is in a pose, where a joint of the robot represented in the image data has an expected joint position when the robot is in the pose. Based on the image data, an actual joint position of the joint when the robot is in the pose is determined. When it is determined that the actual joint position of the joint is different from the expected joint position of the first joint, an encoder of an actuator associated with the joint is configured based, at least in part, on the actual joint position of the joint.
Systems and methods are described for machine learning model prompt generation based on mobile robot data. A system may obtain log data associated with one or more mobile robots. For example, the log data may include sensor data obtained via one or more sensors of the one or more mobile robots. The system may generate a prompt for a machine learning model, the prompt may be based on an obtained input and may include at least a portion of the log data. For example, the prompt may include one or more questions based on the obtained input. The system may provide the prompt to a computing system and obtain an output from the computing system. The system may instruct performance of one or more actions based on the output.
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 101/15 - Details of software or hardware architectures used for the control of position using artificial intelligence [AI] techniques using machine learning, e.g. neural networks
Some robotic arms may include vacuum-based grippers. Detecting the seal quality between each vacuum assembly of the gripper and a grasped object may enable reactivation of some vacuum assemblies, thereby improving the grasp. One embodiment of a method may include activating each of a plurality of vacuum assemblies of a robotic gripper by supplying a vacuum to each vacuum assembly, determining, for each of the activated vacuum assemblies, a first respective seal quality of the vacuum assembly with a first grasped object, deactivating one or more of the activated vacuum assemblies based, at least in part, on the first respective seal qualities, and reactivating each of the deactivated vacuum assemblies within a reactivation interval.
Methods and apparatus for controlling a robotic gripper of a robotic device are provided. The method includes activating a plurality of vacuum assemblies of the robotic gripper to grasp one or more objects, disabling one or more of the plurality of vacuum assemblies having a seal quality with the one or more objects that is less than a first threshold, assigning a score to each of the one or more disabled vacuum assemblies, reactivating the one or more disabled vacuum assemblies in an order based, at least in part, on the assigned scores, and grasping the one or more objects with the robotic gripper when a grasp quality of the robotic gripper is higher than a second threshold.
A computer-implemented method, executed by data processing hardware of a robot, includes receiving a three-dimensional point cloud of sensor data for a space within an environment about the robot. The method includes receiving a selection input indicating a user-selection of a target object represented in an image corresponding to the space. The target object is for grasping by an end-effector of a robotic manipulator of the robot. The method includes generating a grasp region for the end-effector of the robotic manipulator by projecting a plurality of rays from the selected target object of the image onto the three-dimensional point cloud of sensor data. The method includes determining a grasp geometry for the robotic manipulator to grasp the target object within the grasp region. The method includes instructing the end-effector of the robotic manipulator to grasp the target object within the grasp region based on the grasp geometry.
A method includes receiving sensor data of an environment about a robot and generating a plurality of waypoints and a plurality of edges each connecting a pair of the waypoints. The method includes receiving a target destination for the robot to navigate to and determining a route specification based on waypoints and corresponding edges for the robot to follow for navigating the robot to the target destination selected from waypoints and edges previously generated. For each waypoint, the method includes generating a goal region encompassing the corresponding waypoint and generating at least one constraint region encompassing a goal region. The at least one constraint region establishes boundaries for the robot to remain within while traversing toward the target destination. The method includes navigating the robot to the target destination by traversing the robot through each goal region while maintaining the robot within the at least one constraint region.
A robot comprises a mobile base, a robotic arm operatively coupled to the mobile base, and at least one interface configured to enable selective coupling to at least one accessory. The at least one interface comprises an electrical interface configured to transmit power and/or data between the robot and the at least one accessory, and a mechanical interface configured to enable physical coupling between the robot and the at least one accessory.
B25J 15/04 - Gripping heads with provision for the remote detachment or exchange of the head or parts thereof
B25J 5/00 - Manipulators mounted on wheels or on carriages
B25J 19/00 - Accessories fitted to manipulators, e.g. for monitoring, for viewingSafety devices combined with or specially adapted for use in connection with manipulators
Systems and methods are described for combining sensor data obtained by a mobile robot. A system can obtain first sensor data from one or more first sensors of a robot. The system can determine a distance between the robot and at least a portion of the environment based on the first sensor data. For example, the distance may be a depth from a depth map. The system can obtain second sensor data from one or more second sensors of the robot. The system can combine a first portion of the second sensor data and a second portion of the second sensor data based on the distance. For example, the system can use the distance to determine a seam for combination of the first image and the second image. The system can instruct output of a user interface based on the combination.
Systems and methods are described for provision of alerts. A system can obtain sensor data associated with an environment. The system can obtain an input indicating one or more filter parameters, one or more requests, and/or one or more alert parameters. For example, the input may indicate a request, a region of the environment, a region of sensor data, etc. The system can filter the sensor data based on the one or more filter parameters to obtain a filtered portion of the sensor data. The system may generate a prompt for a machine learning model that includes the filtered portion of the sensor data, the one or more requests, and the one or more alert parameters. The system can provide the prompt to a computing system. The system can obtain a output from the computing system and can provide an alert based on the output.
G05D 101/15 - Details of software or hardware architectures used for the control of position using artificial intelligence [AI] techniques using machine learning, e.g. neural networks
G05D 105/80 - Specific applications of the controlled vehicles for information gathering, e.g. for academic research
G05D 107/70 - Industrial sites, e.g. warehouses or factories
Systems and methods are described for provision of alerts. A system can obtain sensor data associated with an environment. The system can obtain an input indicating one or more filter parameters, one or more requests, and/or one or more alert parameters. For example, the input may indicate a request, a region of the environment, a region of sensor data, etc. The system can filter the sensor data based on the one or more filter parameters to obtain a filtered portion of the sensor data. The system may generate a prompt for a machine learning model that includes the filtered portion of the sensor data, the one or more requests, and the one or more alert parameters. The system can provide the prompt to a computing system. The system can obtain a output from the computing system and can provide an alert based on the output.
Systems and methods are described for mapping and traversal of a set of stairs. A system can obtain a map of an environment. The system can determine that the environment includes a set of stairs based on the map. For example, the map may indicate the presence of the set of stairs within the environment. For mapping the set of stairs, the system can instruct performance of a stair mapping maneuver based on the determination that the environment includes the set of stairs. Based on the performance of the stair mapping maneuver, the system can map the set of stairs. The system can instruct traversal of the set of stairs by a robot based on the mapping of the set of stairs.
G05D 1/435 - Control of position or course in two dimensions resulting in a change of level, e.g. negotiating lifts or stairs
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
G05B 19/4155 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by programme execution, i.e. part programme or machine function execution, e.g. selection of a programme
Systems and methods are described for docking a legged robot. A system can obtain sensor data from one or more sensors of the legged robot. The system can obtain dock association data associated with the legged robot. The dock association data may indicate an association of two or more docks to the legged robot. Based on the dock association data, the system can identify a dock of the two or more docks. The system can instruct the legged robot to perform a docking maneuver relative to the dock based on the sensor data and based on identifying the dock. For example, the system can instruct the legged robot to dock at the dock.
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
Systems and methods for semantic robot hazard avoidance with multi-modal prompting are provided. In one aspect, a method includes receiving a user input indicative of one or more hazards in an environment of the robot and image data indicative of the one or more hazards in the environment. The method also includes generating one or more segments of the image data. Each of the one or more segments corresponds to at least one of the one or more hazards indicated by the user input. The method further includes identifying a semantic label for each of the one or more segments, generating a hazard map including a location of each of the one or more segments and the corresponding semantic label, and navigating the robot through the environment based at least in part on the hazard map.
Systems and methods for semantic robot hazard avoidance with multi-modal prompting are provided. In one aspect, a method includes receiving a user input indicative of one or more hazards in an environment of the robot and image data indicative of the one or more hazards in the environment. The method also includes generating one or more segments of the image data. Each of the one or more segments corresponds to at least one of the one or more hazards indicated by the user input. The method further includes identifying a semantic label for each of the one or more segments, generating a hazard map including a location of each of the one or more segments and the corresponding semantic label, and navigating the robot through the environment based at least in part on the hazard map.
A computer-implemented method executed by data processing hardware of a robot causes the data processing hardware to perform operations. The operations include receiving a sensor pointing command that commands the robot to use a sensor to capture sensor data of a location in an environment of the robot. The sensor is disposed on the robot. The operations include determining, based on an orientation of the sensor relative to the location, a direction for pointing the sensor toward the location, and an alignment pose of the robot to cause the sensor to point in the direction toward the location. The operations include commanding the robot to move from a current pose to the alignment pose. After the robot moves to the alignment pose and the sensor is pointing in the direction toward the location, the operations include commanding the sensor to capture the sensor data of the location in the environment.
The operations of a computer-implemented method include obtaining a topological map of an environment including a series of waypoints and a series of edges. Each edge topologically connects a corresponding pair of adjacent waypoints. The edges represent traversable routes for a robot. The operations include determining, using the topological map and sensor data captured by the robot, one or more candidate alternate edges. Each candidate alternate edge potentially connects a corresponding pair of waypoints that are not connected by one of the edges. For each respective candidate alternate edge, the operations include determining, using the sensor data, whether the robot can traverse the respective candidate alternate edge without colliding with an obstacle and, when the robot can traverse the respective candidate alternate edge, confirming the respective candidate alternate edge as a respective alternate edge. The operations include updating, using nonlinear optimization and the confirmed alternate edges, the topological map.
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G01C 22/00 - Measuring distance traversed on the ground by vehicles, persons, animals or other moving solid bodies, e.g. using odometers or using pedometers
G05D 1/246 - Arrangements for determining position or orientation using environment maps, e.g. simultaneous localisation and mapping [SLAM]
G05D 1/644 - Optimisation of travel parameters, e.g. of energy consumption, journey time or distance
G06F 18/2132 - Feature extraction, e.g. by transforming the feature spaceSummarisationMappings, e.g. subspace methods based on discrimination criteria, e.g. discriminant analysis
G06F 18/2134 - Feature extraction, e.g. by transforming the feature spaceSummarisationMappings, e.g. subspace methods based on separation criteria, e.g. independent component analysis
G06F 18/2135 - Feature extraction, e.g. by transforming the feature spaceSummarisationMappings, e.g. subspace methods based on approximation criteria, e.g. principal component analysis
32.
SEMANTIC MODELS FOR ROBOT AUTONOMY ON DYNAMIC SITES
A method includes receiving, while a robot traverses a building environment, sensor data captured by one or more sensors of the robot. The method includes receiving a building information model (BIM) for the environment that includes semantic information identifying one or more permanent objects within the environment. The method includes generating a plurality of localization candidates for a localization map of the environment. Each localization candidate corresponds to a feature of the environment identified by the sensor data and represents a potential localization reference point. The localization map is configured to localize the robot within the environment when the robot moves throughout the environment. For each localization candidate, the method includes determining whether the respective feature corresponding to the respective localization candidate is a permanent object in the environment and generating the respective localization candidate as a localization reference point in the localization map for the robot.
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
G01C 21/00 - NavigationNavigational instruments not provided for in groups
G05D 1/246 - Arrangements for determining position or orientation using environment maps, e.g. simultaneous localisation and mapping [SLAM]
G05D 1/617 - Safety or protection, e.g. defining protection zones around obstacles or avoiding hazards
G05D 111/50 - Internal signals, i.e. from sensors located in the vehicle, e.g. from compasses or angular sensors
An example method may include i) determining a first distance between a pair of feet of a robot at a first time, where the pair of feet is in contact with a ground surface; ii) determining a second distance between the pair of feet of the robot at a second time, where the pair of feet remains in contact with the ground surface from the first time to the second time; iii) comparing a difference between the determined first and second distances to a threshold difference; iv) determining that the difference between determined first and second distances exceeds the threshold difference; and v) based on the determination that the difference between the determined first and second distances exceeds the threshold difference, causing the robot to react.
B62D 57/02 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members
B25J 13/08 - Controls for manipulators by means of sensing devices, e.g. viewing or touching devices
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
G05D 1/245 - Arrangements for determining position or orientation using dead reckoning
G05D 1/43 - Control of position or course in two dimensions
A computer-implemented method when executed by data processing hardware causes the data processing hardware to perform operations. The operations include detecting a candidate support surface at an elevation less than a current surface supporting a legged robot. A determination is made on whether the candidate support surface includes an area of missing terrain data within a portion of an environment surrounding the legged robot, where the area is large enough to receive a touchdown placement for a leg of the legged robot. If missing terrain data is determined, at least a portion of the area of missing terrain data is classified as a no-step region of the candidate support surface. The no-step region indicates a region where the legged robot should avoid touching down a leg of the legged robot.
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
Methods and apparatus for navigating a robot along a route through an environment, the route being associated with a mission, are provided. The method comprises identifying, based on sensor data received by one or more sensors of the robot, a set of potential obstacles in the environment, determining, based at least in part on stored data indicating a set of footfall locations of the robot during a previous execution of the mission, that at least one of the potential obstacles in the set is an obstacle, and navigating the robot to avoid stepping on the obstacle.
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
G05D 1/43 - Control of position or course in two dimensions
G05D 1/617 - Safety or protection, e.g. defining protection zones around obstacles or avoiding hazards
G05D 1/628 - Obstacle avoidance following the obstacle profile, e.g. a wall or undulated terrain
A method for generating intermediate waypoints for a navigation system of a robot includes receiving a navigation route. The navigation route includes a series of high-level waypoints that begin at a starting location and end at a destination location and is based on high-level navigation data. The high-level navigation data is representative of locations of static obstacles in an area the robot is to navigate. The method also includes receiving image data of an environment about the robot from an image sensor and generating at least one intermediate waypoint based on the image data. The method also includes adding the at least one intermediate waypoint to the series of high-level waypoints of the navigation route and navigating the robot from the starting location along the series of high-level waypoints and the at least one intermediate waypoint toward the destination location.
Methods and apparatus for controlling a mobile robot to perform an action are provided. The method includes receiving, by at least one computing device associated with a mobile robot, first sensor data and second sensor data, providing as input to at least one machine learning model, the first sensor data, the second sensor data, and camera intrinsics associated with at least one camera configured to sense the first sensor data and/or the second sensor data, wherein the at least one machine learning model is trained to output polyhedron information representing a set of objects in an environment of the mobile robot, and controlling the mobile robot to perform an action based, at least in part, on the polyhedron information output from the at least one machine learning model.
A robot configured to operate safely in response to detecting an abnormal operating condition is provided. The robot includes an actuator coupled to a robot member and a motor controller configured to control the actuator to move the robot member about a robot joint. The motor controller includes a first set of components and a second set of components, and each of the first set of components and the second set of components is independently operable by the motor controller to control the actuator to move the robot member about the robot joint.
B25J 19/00 - Accessories fitted to manipulators, e.g. for monitoring, for viewingSafety devices combined with or specially adapted for use in connection with manipulators
Methods and apparatus for assigning a quality metric to an object to be grasped by a mobile robot are provided. The method includes receiving at least one image including a set of objects, processing the at least one image using a trained machine learning model to assign a quality metric to a first object of the set of objects in the at least one image, and controlling the mobile robot to perform an action based, at least in part, on the quality metric assigned to the first object.
G05D 101/15 - Details of software or hardware architectures used for the control of position using artificial intelligence [AI] techniques using machine learning, e.g. neural networks
G05D 107/70 - Industrial sites, e.g. warehouses or factories
G06V 10/70 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning
G06V 10/98 - Detection or correction of errors, e.g. by rescanning the pattern or by human interventionEvaluation of the quality of the acquired patterns
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
41.
SLIP HANDLING AND GROUND FRICTION ESTIMATION FOR ROBOTS
Apparatus and methods for mitigating slip conditions and estimating ground friction for a robot having a plurality of feet are provided. In one aspect, a method includes estimating a coefficient of friction for a ground surface supporting the legged robot based on sensor data, odometry data, and a terrain map of an environment. The sensor data includes a set of joint angles and a set of joint torques for a set of joints of the legged robot, and the odometry data indicates a location of the legged robot in the environment. One of the plurality of feet of the robot applies a force on the ground surface based on the estimated coefficient of friction.
Methods and apparatus for determining a velocity of a conveyor associated with a mobile robot are provided. The method includes receiving first image data, the first image data including a first representation of a first object and a conveyor, the first image data captured at a first time, and determining by at least one hardware processor, a velocity of the conveyor based, at least in part, on the first representation of the first object in the first image data and a difference between the first time and a second time different from the first time.
Methods and apparatus for assigning a quality metric to an object to be grasped by a mobile robot are provided. The method includes receiving at least one image including a set of objects, processing the at least one image using a trained machine learning model to assign a quality metric to a first object of the set of objects in the at least one image, and controlling the mobile robot to perform an action based, at least in part, on the quality metric assigned to the first object.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
The invention includes systems and methods for determining movement of a robot. A computing system of the robot receives information comprising a reference behavior specification, a current state of the robot, and a characteristic of a massive body coupled to or expected to be coupled to the robot. The computing system determines, based on the information, a set of movement parameters for the robot, the set of movement parameters reflecting a goal trajectory for the robot. The computing system instructs the robot to move consistent with the set of movement parameters.
A method of constrained mobility mapping includes receiving from at least one sensor of a robot at least one original set of sensor data and a current set of sensor data. Here, each of the at least one original set of sensor data and the current set of sensor data corresponds to an environment about the robot. The method further includes generating a voxel map including a plurality of voxels based on the at least one original set of sensor data. The method also includes generating a spherical depth map based on the current set of sensor data and determining that a change has occurred to an obstacle represented by the voxel map based on a comparison between the voxel map and the spherical depth map. The method additional includes updating the voxel map to reflect the change to the obstacle.
B25J 13/08 - Controls for manipulators by means of sensing devices, e.g. viewing or touching devices
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
G05D 1/243 - Means capturing signals occurring naturally from the environment, e.g. ambient optical, acoustic, gravitational or magnetic signals
A computer-implemented method executed by data processing hardware of a robot causes the data processing hardware to perform operations including obtaining a topological map including waypoints and edges. Each edge connects adjacent waypoints. The waypoints and edges represent a navigation route for the robot to follow. Operations include determining, that an edge that connects first and second waypoints is blocked by an obstacle. Operations include generating, using image data and the topological map, one or more alternate waypoints offset from one of the waypoints. For each alternate waypoint, operations include generating an alternate edge connecting the alternate waypoint to a waypoint. Operations include adjusting the navigation route to include at least one alternate waypoint and alternate edge that bypass the obstacle. Operations include navigating the robot from the first waypoint to an alternate waypoint along the alternate edge connecting the alternate waypoint to the first waypoint.
An example implementation for determining mechanically-timed footsteps may involve a robot having a first foot in contact with a ground surface and a second foot not in contact with the ground surface. The robot may determine a position of its center of mass and center of mass velocity, and based on these, determine a capture point for the robot. The robot may also determine a threshold position for the capture point, where the threshold position is based on a target trajectory for the capture point after the second foot contacts the ground surface. The robot may determine that the capture point has reached this threshold position and based on this determination, and cause the second foot to contact the ground surface.
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
Methods and apparatus for controlling a robot (e.g., having a set of continuous rotation joints) to perform extra human behaviors are provided. The method includes receiving task information to perform a task, determining, using a control system of the robot, a motion plan for the robot to perform the task, wherein the motion plan includes rotation about one or more joints of the robot (e.g., about at least one of the continuous rotation joints in the set of continuous rotation joints) to efficiently perform the task using extra human behaviors.
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
Methods and apparatus for controlling a robot (e.g., having a set of continuous rotation joints) to perform extra human behaviors are provided. The method includes receiving task information to perform a task, determining, using a control system of the robot, a motion plan for the robot to perform the task, wherein the motion plan includes rotation about one or more joints of the robot (e.g., about at least one of the continuous rotation joints in the set of continuous rotation joints) to efficiently perform the task using extra human behaviors.
A sensor module for an end effector of a robot is described. The sensor module includes a substrate having formed thereon, a set of proximity sensors and a set of pressure sensors, the set of proximity sensors and the set of pressure sensors configured to have overlapping sensing regions, and a cover coupled to the substrate, the cover comprising a material that permits transmission of signals from the set of proximity sensors through the material.
A method for online authoring of robot autonomy applications includes receiving sensor data of an environment about a robot while the robot traverses through the environment. The method also includes generating an environmental map representative of the environment about the robot based on the received sensor data. While generating the environmental map, the method includes localizing a current position of the robot within the environmental map and, at each corresponding target location of one or more target locations within the environment, recording a respective action for the robot to perform. The method also includes generating a behavior tree for navigating the robot to each corresponding target location and controlling the robot to perform the respective action at each corresponding target location within the environment during a future mission when the current position of the robot within the environmental map reaches the corresponding target location.
Methods and apparatus for implementing signaling in access point devices is described. An access point device may include a network interface configured to be coupled to a wired network, a radio configured to emit radio waves that enable a plurality of wireless devices in an environment of the access point device to wirelessly access the wired network, and at least one signaling component, wherein the at least one signaling component is configured to transmit and/or receive signals, wherein the signals are different from the radio waves emitted from the radio.
H04W 4/38 - Services specially adapted for particular environments, situations or purposes for collecting sensor information
H04W 4/80 - Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
Methods and apparatus for implementing signaling in access point devices is described. An access point device may include a network interface configured to be coupled to a wired network, a radio configured to emit radio waves that enable a plurality of wireless devices in an environment of the access point device to wirelessly access the wired network, and at least one signaling component, wherein the at least one signaling component is configured to transmit and/or receive signals, wherein the signals are different from the radio waves emitted from the radio.
G05D 1/69 - Coordinated control of the position or course of two or more vehicles
G05D 105/28 - Specific applications of the controlled vehicles for transportation of freight
G05D 107/70 - Industrial sites, e.g. warehouses or factories
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
H04W 4/33 - Services specially adapted for particular environments, situations or purposes for indoor environments, e.g. buildings
H04W 76/15 - Setup of multiple wireless link connections
A computer-implemented method executed by data processing hardware of a robot causes the data processing hardware to perform operations. The robot includes an articulated arm having an end effector configured to engage with an object. The operations include receiving a measured task parameter set for the end effector. The measured task parameter set representing positions of the end effector while manipulating the object. The operations also include generating a task space model for the object based on the measured task parameter set. The task space model modelling the at least one constrained axis of the object. The operations further include limiting movement of the end effector along the at least one constrained axis of the object based on the task space model.
B25J 13/08 - Controls for manipulators by means of sensing devices, e.g. viewing or touching devices
B62D 57/02 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members
G05B 19/4155 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by programme execution, i.e. part programme or machine function execution, e.g. selection of a programme
56.
DIRECTED EXPLORATION FOR NAVIGATION IN DYNAMIC ENVIRONMENTS
A computer-implemented method when executed by data processing hardware causes the data processing hardware to perform operations. The operations include receiving a navigation route for a mobile robot. The navigation route includes a sequence of waypoints connected by edges. Each edge corresponds to movement instructions that navigate the mobile robot between waypoints of the sequence of waypoints. While the mobile robot is traveling along the navigation route, the operations include determining that the mobile robot is unable to execute a respective movement instruction for a respective edge of the navigation route due to an obstacle obstructing the respective edge, generating an alternative path to navigate the mobile robot to an untraveled waypoint in the sequence of waypoints, and resuming travel by the mobile robot along the navigation route. The alternative path avoids the obstacle.
A method of footstep contact detection includes receiving joint dynamics data for a swing phase of a swing leg of the robot, receiving odometry data indicative of a pose of the robot, determining whether an impact on the swing leg is indicative of a touchdown of the swing leg based on the joint dynamics data and an amount of completion of the swing phase, and determining when the impact on the swing leg is not indicative of the touchdown of the swing leg, a cause of the impact based on the joint dynamics data and the odometry data.
B25J 13/08 - Controls for manipulators by means of sensing devices, e.g. viewing or touching devices
B62D 57/02 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members
B62D 57/024 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members specially adapted for moving on inclined or vertical surfaces
B62D 57/028 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members having wheels and mechanical legs
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
59.
SCREW ACTUATOR, A ROBOR COMPRISING THE SCREW ACTUATOR AND A METHOD
The invention includes a screw actuator. The screw actuator includes a screw having a screw shaft and a screw nut. The screw shaft defines a first longitudinal axis along its length. The screw nut at least partially surrounds the screw shaft. The screw actuator includes a motor having a stator and a rotor. The rotor is mechanically coupled to the screw shaft. The stator at least partially surrounds the rotor. The screw actuator includes a first rigid member having a length dimension oriented along the first longitudinal axis. The screw actuator includes a second rigid member mechanically constrained relative to the first rigid member. The second rigid member is configured to move along a direction of the first longitudinal axis.
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
A computing system of a robot receives robot data reflecting at least a portion of the robot, and object data reflecting at least a portion of an object, the object data determined based on information from at least two sources. The computing system determines, based on the robot data and the object data, a set of states of the object, each state in the set of states associated with a distinct time at which the object is at least partially supported by the robot. The set of states includes at least three states associated with three distinct times. The computing system instructs the robot to perform a manipulation of the object based, at least in part, on at least one state in the set of states.
Systems and methods are described for instructing performance of a localization and an action by a mobile robot based on composite data. A system may obtain satellite-based position data and one or more of odometry data or point cloud data. The system may generate composite data by merging the satellite-based position data and the one or more of the odometry data or the point cloud data. The system may instruct performance of a localization by the mobile robot based on the composite data. Based on the localization by the mobile robot, the system may identify an action and instruct performance of the action by a mobile robot.
G05D 1/246 - Arrangements for determining position or orientation using environment maps, e.g. simultaneous localisation and mapping [SLAM]
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
G01S 19/45 - Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
G05D 1/222 - Remote-control arrangements operated by humans
G05D 1/648 - Performing a task within a working area or space, e.g. cleaning
G05D 111/50 - Internal signals, i.e. from sensors located in the vehicle, e.g. from compasses or angular sensors
Techniques for automated constrained manipulation are provided. In one aspect, a method includes receiving a request for manipulating a target constrained object and receiving perception data from at least one sensor of a robot. The perception data indicative of the target constrained object. The method also includes receiving a semantic model of the target constrained object generated based on the perception data and determining a location for a robotic arm of the robot to interact with the target constrained object based on the semantic model and the request. The method further includes controlling the robotic arm to manipulate the target constrained object based on the location for the robotic arm to interact with the target constrained object.
Methods and apparatus for determining a control strategy for controlling a robot based on power limits of the robot are provided. The method includes determining, by a computing device, motor control information for a plurality of motors associated with a plurality of joints of the robot, the motor control information being determined based, at least in part, on a robot trajectory to achieve a desired behavior and power limit information associated with a power system of the robot, and controlling the plurality of motors associated with the plurality of joints of the robot based, at least in part, on the motor control information.
G05D 1/646 - Following a predefined trajectory, e.g. a line marked on the floor or a flight path
B60L 15/20 - Methods, circuits or devices for controlling the propulsion of electrically-propelled vehicles, e.g. their traction-motor speed, to achieve a desired performanceAdaptation of control equipment on electrically-propelled vehicles for remote actuation from a stationary place, from alternative parts of the vehicle or from alternative vehicles of the same vehicle train for control of the vehicle or its driving motor to achieve a desired performance, e.g. speed, torque, programmed variation of speed
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
The invention includes systems and methods for relating to improved body structures for robots. A robot assembly includes a base member (e.g., a pelvis base). The robot assembly includes a first hip member rotatably connected to the pelvis base. The first hip member is connected to a first electric actuator configured to rotate the first hip member about a first hip axis relative to the pelvis base. A first intermediate member is rotatably connected to the first hip member. The first intermediate member is connected to a second electric actuator configured to rotate the first intermediate member about a second hip axis relative to the first hip member. A first leg member is rotatably connected to the first intermediate member. The first leg member is connected to a third electric actuator configured to rotate the first leg member about a third hip axis relative to the first intermediate member.
Computer-implemented methods and apparatus for manipulating an object using a robotic device are provided. The method includes associating a first grasp region of an object with an end effector of a robotic device, wherein the first grasp region includes a set of potential grasps achievable by the end effector of the robotic device. The method further includes determining, within the first grasp region, a grasp from among the set of potential grasps, wherein the grasp is determined based, at least in part, on information associated with a capability of the robotic device to perform the grasp, and instructing the robotic device to manipulate the object based on the grasp.
The invention includes a screw actuator. The screw actuator includes a screw having a screw shaft and a screw nut. The screw shaft defines a first longitudinal axis along its length. The screw nut at least partially surrounds the screw shaft. The screw actuator includes a motor having a stator and a rotor. The rotor is mechanically coupled to the screw shaft. The stator at least partially surrounds the rotor. The screw actuator includes a first rigid member having a length dimension oriented along the first longitudinal axis. The screw actuator includes a second rigid member mechanically constrained relative to the first rigid member. The second rigid member is configured to move along a direction of the first longitudinal axis.
Systems and methods are disclosed for altering operation of a machine (e.g., bringing about an emergency stop). A device comprises an emitter configured to produce a first acoustic signal having a first tone and a second tone, wherein the first tone is different from the second tone. The device also includes an activation mechanism in communication with the emitter. The activation mechanism is configured to activate the emitter.
Techniques for automated constrained manipulation are provided. In one aspect, a method includes receiving a request for manipulating a target constrained object and receiving perception data from at least one sensor of a robot. The perception data indicative of the target constrained object. The method also includes receiving a semantic model of the target constrained object generated based on the perception data and determining a location for a robotic arm of the robot to interact with the target constrained object based on the semantic model and the request. The method further includes controlling the robotic arm to manipulate the target constrained object based on the location for the robotic arm to interact with the target constrained object.
Systems and methods are described for dynamic and variable definition of robot missions and performance of the robot missions. A system can obtain first robot mission data associated with a first robot mission and second robot mission data. The second robot mission data may be associated with a second robot mission or a user-defined route edge. The system can generate composite mission data based on the first robot mission data and the second robot mission data. The system can instruct navigation of a robot through an environment according to the composite mission data.
Systems and methods are disclosed for altering operation of a machine (e.g., bringing about an emergency stop). A device comprises an emitter configured to produce a first acoustic signal having a first tone and a second tone, wherein the first tone is different from the second tone. The device also includes an activation mechanism in communication with the emitter. The activation mechanism is configured to activate the emitter.
G05B 19/406 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by monitoring or safety
F16P 3/14 - Safety devices acting in conjunction with the control or operation of a machineControl arrangements requiring the simultaneous use of two or more parts of the body with means, e.g. feelers, which in case of the presence of a body part of a person in or near the danger zone influence the control or operation of the machine the means being photocells or other devices sensitive without mechanical contact
71.
ROBOT LOCALIZATION USING DATA WITH VARIABLE DATA TYPES
Systems and methods are described for instructing performance of a localization and an action by a mobile robot based on composite data. A system may obtain satellite-based position data and one or more of odometry data or point cloud data. The system may generate composite data by merging the satellite-based position data and the one or more of the odometry data or the point cloud data. The system may instruct performance of a localization by the mobile robot based on the composite data. Based on the localization by the mobile robot, the system may identify an action and instruct performance of the action by a mobile robot.
G01C 21/00 - NavigationNavigational instruments not provided for in groups
G05D 1/245 - Arrangements for determining position or orientation using dead reckoning
G05D 1/246 - Arrangements for determining position or orientation using environment maps, e.g. simultaneous localisation and mapping [SLAM]
G05D 1/248 - Arrangements for determining position or orientation using signals provided by artificial sources external to the vehicle, e.g. navigation beacons generated by satellites, e.g. GPS
G05D 107/17 - Spaces with priority for humans, e.g. populated areas, pedestrian ways, parks or beaches
G05D 107/60 - Open buildings, e.g. offices, hospitals, shopping areas or universities
The invention includes a screw actuator. The screw actuator includes a screw having a screw shaft and a screw nut. The screw shaft defines a first longitudinal axis along its length. The screw nut at least partially surrounds the screw shaft. The screw actuator includes a motor having a stator and a rotor. The rotor is mechanically coupled to the screw shaft. The stator at least partially surrounds the rotor. The screw actuator includes a first rigid member having a length dimension oriented along the first longitudinal axis. The screw actuator includes a second rigid member mechanically constrained relative to the first rigid member. The second rigid member is configured to move along a direction of the first longitudinal axis.
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
H02K 7/06 - Means for converting reciprocating motion into rotary motion or vice versa
F16H 25/22 - Screw mechanisms with balls, rollers, or similar members between the co-operating partsElements essential to the use of such members
Systems and methods related to intelligent grippers with individual cup control are disclosed. One aspect of the disclosure provides a method of determining grip quality between a robotic gripper and an object. The method comprises applying a vacuum to two or more cup assemblies of the robotic gripper in contact with the object, moving the object with the robotic gripper after applying the vacuum to the two or more cup assemblies, and determining, using at least one pressure sensor associated with each of the two or more cup assemblies, a grip quality between the robotic gripper and the object.
A robot includes a mobile base, a turntable rotatably coupled to the mobile base, a robotic arm operatively coupled to the turntable, and at least one directional sensor. An orientation of the at least one directional sensor is independently controllable. A method of controlling a robotic arm includes controlling a state of a mobile base and controlling a state of a robotic arm coupled to the mobile base, based, at least in part, on the state of the mobile base.
Systems and methods for determining movement of a robot about an environment are provided. A computing system of the robot (i) receives information including a navigation target for the robot and a kinematic state of the robot; (ii) determines, based on the information and a trajectory target for the robot, a retargeted trajectory for the robot; (iii) determines, based on the retargeted trajectory, a centroidal trajectory for the robot and a kinematic trajectory for the robot consistent with the centroidal trajectory; and (iv) determines, based on the centroidal trajectory and the kinematic trajectory, a set of vectors having a vector for each of one or more joints of the robot.
B25J 13/08 - Controls for manipulators by means of sensing devices, e.g. viewing or touching devices
B62D 57/02 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members
G05D 1/249 - Arrangements for determining position or orientation using signals provided by artificial sources external to the vehicle, e.g. navigation beacons from positioning sensors located off-board the vehicle, e.g. from cameras
G05D 1/646 - Following a predefined trajectory, e.g. a line marked on the floor or a flight path
76.
DYNAMIC MASS ESTIMATION METHODS FOR AN INTEGRATED MOBILE MANIPULATOR ROBOT
A method of estimating one or more mass characteristics of a payload manipulated by a robot includes moving the payload using the robot, determining one or more accelerations of the payload while the payload is in motion, sensing, using one or more sensors of the robot, a wrench applied to the payload while the payload is in motion, and estimating the one or more mass characteristics of the payload based, at least in part, on the determined accelerations and the sensed wrench.
An example implementation includes (i) receiving sensor data that indicates topographical features of an environment in which a robotic device is operating, (ii) processing the sensor data into a topographical map that includes a two-dimensional matrix of discrete cells, the discrete cells indicating sample heights of respective portions of the environment, (iii) determining, for a first foot of the robotic device, a first step path extending from a first lift-off location to a first touch-down location, (iv) identifying, within the topographical map, a first scan patch of cells that encompass the first step path, (v) determining a first high point among the first scan patch of cells; and (vi) during the first step, directing the robotic device to lift the first foot to a first swing height that is higher than the determined first high point.
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
G05D 1/43 - Control of position or course in two dimensions
G05D 1/646 - Following a predefined trajectory, e.g. a line marked on the floor or a flight path
78.
HANDLING GAIT DISTURBANCES WITH ASYNCHRONOUS TIMING
An example method may include i) detecting a disturbance to a gait of a robot, where the gait includes a swing state and a step down state, the swing state including a target swing trajectory for a foot of the robot, and where the target swing trajectory includes a beginning and an end; and ii) based on the detected disturbance, causing the foot of the robot to enter the step down state before the foot reaches the end of the target swing trajectory.
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
A method for terrain and constraint planning a step plan includes receiving, at data processing hardware of a robot, image data of an environment about the robot from at least one image sensor. The robot includes a body and legs. The method also includes generating, by the data processing hardware, a body-obstacle map, a ground height map, and a step-obstacle map based on the image data and generating, by the data processing hardware, a body path for movement of the body of the robot while maneuvering in the environment based on the body-obstacle map. The method also includes generating, by the data processing hardware, a step path for the legs of the robot while maneuvering in the environment based on the body path, the body-obstacle map, the ground height map, and the step-obstacle map.
Techniques for determining robotic step timing and sequencing using reinforcement learning are provided. In one aspect, a method includes receiving a target trajectory for a robot and receiving a state of the robot. The method further includes generating, using a neural network, a set of gait timing parameters for the robot based, at least in part, on the state of the robot and the target trajectory and controlling movement of the robot based on the set of gait timing parameters.
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
G05D 101/15 - Details of software or hardware architectures used for the control of position using artificial intelligence [AI] techniques using machine learning, e.g. neural networks
Techniques for determining robotic step timing and sequencing using reinforcement learning are provided. In one aspect, a method includes receiving a target trajectory for a robot and receiving a state of the robot. The method further includes generating, using a neural network, a set of gait timing parameters for the robot based, at least in part, on the state of the robot and the target trajectory and controlling movement of the robot based on the set of gait timing parameters.
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
Methods and apparatus for grasping an object by a suction-based gripper of a mobile robot are provided. The method comprises receiving, by a computing device, from a perception system of the mobile robot, perception information reflecting an object to be grasped by the suction-based gripper, determining, by the computing device, uncertainty information reflecting an unknown or uncertain extent and/or pose of the object, determining, by the computing device, a grasp strategy to grasp the object based, at least in part, on the uncertainty information, and controlling, by the computing device, the mobile robot to grasp the object using the grasp strategy.
Systems and methods for determining movement of a robot are provided. A computing system of the robot receives information including an initial state of the robot and a goal state of the robot. The computing system determines, using nonlinear optimization, a candidate trajectory for the robot to move from the initial state to the goal state. The computing system determines whether the candidate trajectory is feasible. If the candidate trajectory is feasible, the computing system provides the candidate trajectory to a motion control module of the robot. If the candidate trajectory is not feasible, the computing system determines, using nonlinear optimization, a different candidate trajectory for the robot to move from the initial state to the goal state, the nonlinear optimization using one or more changed parameters.
A method for negotiating stairs includes receiving image data about a robot maneuvering in an environment with stairs. Here, the robot includes two or more legs. Prior to the robot traversing the stairs, for each stair, the method further includes determining a corresponding step region based on the received image data. The step region identifies a safe placement area on a corresponding stair for a distal end of a corresponding swing leg of the robot. Also prior to the robot traversing the stairs, the method includes shifting a weight distribution of the robot towards a front portion of the robot. When the robot traverses the stairs, the method further includes, for each stair, moving the distal end of the corresponding swing leg of the robot to a target step location where the target step location is within the corresponding step region of the stair.
B62D 57/024 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members specially adapted for moving on inclined or vertical surfaces
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
85.
WHOLE BODY MANIPULATION ON A LEGGED ROBOT USING DYNAMIC BALANCE
A robot system includes: an upper body section including one or more end-effectors; a lower body section including one or more legs; and an intermediate body section coupling the upper and lower body sections. An upper body control system operates at least one of the end-effectors. The intermediate body section experiences a first intermediate body linear force and/or moment based on an end-effector force acting on the at least one end-effector. A lower body control system operates the one or more legs. The one or more legs experience respective surface reaction forces. The intermediate body section experiences a second intermediate body linear force and/or moment based on the surface reaction forces. The lower body control system operates the one or more legs so that the second intermediate body linear force balances the first intermediate linear force and the second intermediate body moment balances the first intermediate body moment.
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
B62D 57/02 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members
B62D 57/024 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members specially adapted for moving on inclined or vertical surfaces
86.
DYNAMIC PERFORMANCE OF ACTIONS BY A MOBILE ROBOT BASED ON SENSOR DATA AND A SITE MODEL
Systems and methods are described for instructing performance of an action by a mobile robot based on transformed data. A system may obtain a site model in a first data format and sensor data in a second data format. The site model and/or the sensor data may be annotated. The system may transform the site model and the sensor data to generate transformed data in a third data format. The system may provide the transformed data to a computing system. For example, the system may provide the transformed data to a machine learning model. Based on the output of the computing system, the system may identify an action and instruct performance of the action by a mobile robot.
Systems and methods are described for instructing performance of an action by a mobile robot based on transformed data. A system may obtain a site model in a first data format and sensor data in a second data format. The site model and/or the sensor data may be annotated. The system may transform the site model and the sensor data to generate transformed data in a third data format. The system may provide the transformed data to a computing system. For example, the system may provide the transformed data to a machine learning model. Based on the output of the computing system, the system may identify an action and instruct performance of the action by a mobile robot.
A gripper mechanism includes a pair of gripper jaws, a linear actuator, and a rocker bogey. The linear actuator drives a first gripper jaw to move relative to a second gripper jaw. Here, the linear actuator includes a screw shaft and a drive nut where the drive nut includes a protrusion having protrusion axis expending along a length of the protrusion. The protrusion axis is perpendicular to an actuation axis of the linear actuator along a length of the screw shaft. The rocker bogey is coupled to the drive nut at the protrusion to form a pivot point for the rocker bogey and to enable the rocker bogey to pivot about the protrusion axis when the linear actuator drives the first gripper jaw to move relative to the second gripper jaw.
The invention includes systems and methods for routing data packets in a robot. The method comprises routing, using a first switching device, data packets between a first host processor and a first electronic device of the robot, and routing, using the first switching device, data packets between a second host processor and a second electronic device of the robot.
A perception mast for mobile robot is provided. The mobile robot comprises a mobile base, a turntable operatively coupled to the mobile base, the turntable configured to rotate about a first axis, an arm operatively coupled to a first location on the turntable, and the perception mast operatively coupled to a second location on the turntable, the perception mast configured to rotate about a second axis parallel to the first axis, wherein the perception mast includes disposed thereon, a first perception module and a second perception module arranged between the first imaging module and the turntable.
A computer-implemented method when executed by data processing hardware of a legged robot causes the data processing hardware to perform operations including receiving sensor data corresponding to an area including at least a portion of a docking station. The operations include determining an estimated pose for the docking station based on an initial pose of the legged robot relative to the docking station. The operations include identifying one or more docking station features from the received sensor data. The operations include matching the one or more identified docking station features to one or more known docking station features. The operations include adjusting the estimated pose for the docking station to a corrected pose for the docking station based on an orientation of the one or more identified docking station features that match the one or more known docking station features.
B60L 53/36 - Means for automatic or assisted adjustment of the relative position of charging devices and vehicles by positioning the vehicle
B60L 53/16 - Connectors, e.g. plugs or sockets, specially adapted for charging electric vehicles
B62D 57/02 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members
The disclosure provides systems and methods for mitigating slip of a robot appendage. In one aspect, a method for mitigating slip of a robot appendage includes (i) receiving an input from one or more sensors, (ii) determining, based on the received input, an appendage position of the robot appendage, (iii) determining a filter position for the robot appendage, (iv) determining a distance between the appendage position and the filter position, (v) determining, based on the distance, a force to apply to the robot appendage, (vi) causing one or more actuators to apply the force to the robot appendage, (vii) determining whether the distance is greater than a threshold distance, and (viii) responsive to determining that the distance is greater than the threshold distance, the control system adjusting the filter position to a position, which is the threshold distance from the appendage position, for use in a next iteration.
B25J 13/08 - Controls for manipulators by means of sensing devices, e.g. viewing or touching devices
B25J 19/00 - Accessories fitted to manipulators, e.g. for monitoring, for viewingSafety devices combined with or specially adapted for use in connection with manipulators
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
93.
SYSTEMS AND METHODS FOR PROVIDING MODULAR ARCHITECTURES FOR ROBOTIC END EFFECTORS
A robotic gripper includes a first modular component comprising a set of deformable members, such as a set of vacuum cups or foam members. The robotic gripper also includes a second modular component comprising a set of vacuum valves. Each vacuum valve in the set of vacuum valves is fluidly connected to at least one deformable member in the set of deformable members.
A robotic gripper includes a first modular component comprising a set of deformable members, such as a set of vacuum cups or foam members. The robotic gripper also includes a second modular component comprising a set of vacuum valves. Each vacuum valve in the set of vacuum valves is fluidly connected to at least one deformable member in the set of deformable members.
A method of manipulating boxes includes receiving a minimum box size for a plurality of boxes varying in size located in a walled container. The method also includes dividing a grip area of a gripper into a plurality of zones. The method further includes locating a set of candidate boxes based on an image from a visual sensor. For each zone, the method additionally includes, determining an overlap of a respective zone with one or more neighboring boxes to the set of candidate boxes. The method also includes determining a grasp pose for a target candidate box that avoids one or more walls of the walled container. The method further includes executing the grasp pose to lift the target candidate box by the gripper where the gripper activates each zone of the plurality of zones that does not overlap a respective neighboring box to the target candidate box.
Systems and methods are described for detecting changes at a location based on image data by a mobile robot. A system can instruct navigation of the mobile robot to a location. For example, the system can instruct navigation to the location as part of an inspection mission. The system can obtain input identifying a change detection. Based on the change detection and obtained image data associated with the location, the system can perform the change detection and detect a change associated with the location. For example, the system can perform the change detection based on one or more regions of interest of the obtained image data. Based on the detected change and a reference model, the system can determine presence of an anomaly condition in the obtained image data.
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legVehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
G05D 1/689 - Pointing payloads towards fixed or moving targets
Systems and methods are described for detecting changes at a location based on image data by a mobile robot. A system can instruct navigation of the mobile robot to a location. For example, the system can instruct navigation to the location as part of an inspection mission. The system can obtain input identifying a change detection. Based on the change detection and obtained image data associated with the location, the system can perform the change detection and detect a change associated with the location. For example, the system can perform the change detection based on one or more regions of interest of the obtained image data. Based on the detected change and a reference model, the system can determine presence of an anomaly condition in the obtained image data.
G05D 1/249 - Arrangements for determining position or orientation using signals provided by artificial sources external to the vehicle, e.g. navigation beacons from positioning sensors located off-board the vehicle, e.g. from cameras
G05D 1/246 - Arrangements for determining position or orientation using environment maps, e.g. simultaneous localisation and mapping [SLAM]
G05D 1/689 - Pointing payloads towards fixed or moving targets
A dynamic planning controller receives a maneuver for a robot and a current state of the robot and transforms the maneuver and the current state of the robot into a nonlinear optimization problem. The nonlinear optimization problem is configured to optimize an unknown force and an unknown position vector. At a first time instance, the controller linearizes the nonlinear optimization problem into a first linear optimization problem and determines a first solution to the first linear optimization problem using quadratic programming. At a second time instance, the controller linearizes the nonlinear optimization problem into a second linear optimization problem based on the first solution at the first time instance and determines a second solution to the second linear optimization problem based on the first solution using the quadratic programming. The controller also generates a joint command to control motion of the robot during the maneuver based on the second solution.
G05B 13/04 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
Systems and methods are described for outputting light and/or audio using one or more light and/or audio sources of a robot. The light sources may be located on one or more legs of the robot, a bottom portion of the robot, and/or a top portion of the robot. The audio sources may include a speaker and/or an audio resonator. A system can obtain sensor data associated with an environment of the robot. Based on the sensor data, the system can identify an alert. For example, the system can identify an entity based on the sensor data and identify an alert for the entity. The system can instruct an output of light and/or audio indicative of the alert using the one or more light and/or audio sources. The system can adjust parameters of the output based on the sensor data.
