The invention is notably directed to end effector (10, 10a) for an automated vehicle charging robot (1). The end effector (10, 10a) comprises: a connecting module (100), which is delimited by a reference plane (P) and is designed to enable a connection of the end effector (10, 10a) to a robotic arm (40) of the charging robot (1) on a first side of the reference plane (P); an electrical connector (106, 108) including a body (108) and a plug (106), the plug designed to connect to a charge port (220) and arranged at an end of the body (108), wherein the body (108) extends from the connecting module (100) to the plug (106) on a second side of the reference plane (P), the second side opposite to said first side, along an extension direction (De) that is transverse to the reference plane (P); and an actuator (114, 115) that protrudes from said body (108), transversely to said extension direction (De), the actuator (114, 115) designed to actuate a door (210) of the vehicle charge port (220). The invention is further directed to: a functionalized robotic arm (40), which includes such an end effector; an automated vehicle charging system (1), which includes such a robotic arm; and a method of electrically charging an electrical vehicle using such a functionalized robotic arm.
B25J 13/08 - Controls for manipulators by means of sensing devices, e.g. viewing or touching devices
B25J 15/04 - Gripping heads with provision for the remote detachment or exchange of the head or parts thereof
B60L 53/16 - Connectors, e.g. plugs or sockets, specially adapted for charging electric vehicles
B60L 53/37 - Means for automatic or assisted adjustment of the relative position of charging devices and vehicles using optical position determination, e.g. using cameras
E05F 15/73 - Power-operated mechanisms for wings with automatic actuation responsive to movement or presence of persons or objects
E05F 15/75 - Power-operated mechanisms for wings with automatic actuation responsive to movement or presence of persons or objects responsive to the weight or other physical contact of a person or object
4.
DETERMINING FEATURE POSES OF ELECTRIC VEHICLES TO AUTOMATICALLY CHARGE ELECTRIC VEHICLES
The invention is notably directed to a computer-implemented method for automatically charging an electric vehicle via an end effector (10) of a robotic arm (40) of an automated vehicle charging robot. The end effector is assumed to be structured so as to be able to connect to a charge port (220) of a vehicle. In addition, the automated vehicle charging robot further includes a camera system (102) having depth sensing capability. The method comprises the following steps. First, a reference position of a reference feature (210) of the vehicle is estimated thanks to the camera system. Next, a pose of the charge port of the vehicle is determined based on the estimated reference position. The robotic arm is subsequently instructed to actuate the end effector, based on the determined pose of the charge port, to connect the end effector to the charge port with a view to charging the vehicle. The reference position is estimated as follows. Both a 2D image and a depth image of a surface portion of the vehicle are obtained. This surface portion includes the reference feature, i.e., the feature of interest. Contour points of the reference feature are then extracted from the 2D image obtained. The 3D coordinates of the extracted contour points are subsequently reconstructed based on the depth image obtained. A geometric object (such a 2D plane) is then matched to the reconstructed 3D coordinates, e.g., by fitting the geometric object to the reconstructed 3D coordinates. Eventually, the reference position of the reference feature is determined based on the matched geometric object. The invention is further directed to related automated vehicle charging robots and computer program products.
B60L 53/37 - Means for automatic or assisted adjustment of the relative position of charging devices and vehicles using optical position determination, e.g. using cameras
The invention is notably directed to a method of steering an automated vehicle (2) in a designated area, thanks to a set (10) of offboard perception sensors (110-140). The method comprises repeatedly executing algorithmic iterations, where each iteration comprises the following steps. First, sensor data are dispatched to K processing systems (11, 12), whereby each processing system k of the K processing systems receives Nk datasets of the sensor data as obtained from Nk respective sensors of the set (10) of offboard perception sensors (110-140), where k=1 to K, K≥2, and Nk≥2. The Nk datasets are subsequently processed at each processing system k to obtain Mk occupancy grids corresponding to perceptions from Mk respective sensors of the offboard perception sensors, respectively, where Nk≥Mk≥1. The Mk occupancy grids overlap at least partly. Data from the Mk occupancy grids obtained are then fused, at each processing system k, to form a fused occupancy grid, whereby K fused occupancy grids are formed by the K processing systems (11, 12), respectively. The K fused occupancy grids are then forwarded to a further processing system (14), which merges the K fused occupancy grids to obtain a global occupancy grid for the designated area. Eventually, a trajectory is determined for the automated vehicle (2), based on the global occupancy grid. This trajectory is then forwarded to a drive-by-wire system (20) of the automated vehicle (2), to accordingly steer the latter. The invention is further directed to related systems and computer program products.
The invention is notably directed to a computer-implemented method of steering an automated vehicle in a designated area using a set of one or more offboard sensors. Each of these sensors is preferably a 3D laser scanning Lidar, e.g., an infrastructure-based Lidar. The method comprising repeatedly executing algorithmic iterations, wherein each iteration comprises obtaining (S30) a grid, performing (S200) a revision procedure to revise the grid, and determining (S90) a trajectory for the automated vehicle, based on the revised grid. The grid is obtained (S30) as a 2D occupancy grid of cells. This is achieved by determining a state of each cell in accordance with a perception of the one or more offboard sensors. The aim of the revision procedure (S200) is to revise the obtained grid. The grid is revised by correcting the state determined for each of one or more of the cells based on a history of such a cell. Eventually, the method determines (S90) a trajectory for the automated vehicle, based on the revised grid, and forwards (S100) the determined trajectory to a drive-by-wire system of the automated vehicle, to steer the latter. The invention is further directed to related systems and computer program products.
The invention is notably directed to a computer-implemented method of steering an automated vehicle on a ground of a designated area using a set of one or more offboard sensors (110), each being a 3D laser scanning Lidar. The method comprises repeatedly executing algorithmic iterations. Each iteration of the algorithmic iterations comprises obtaining, for each sensor of the one or more offboard sensors, a grid, which is a 2D occupancy grid of cells reflecting a perception of said each sensor. This is achieved by first accessing a dataset capturing a point cloud model of an environment of said each sensor and processing the dataset to identify characteristics of rays (Ri) emitted by said each sensor, the characteristics including hit points (HPi) of the rays, as well as projections of the hit points and the rays on a plane (G) corresponding to the ground. The grid is populated by determining a state of each cell (Cj) of the cells based on the identified characteristics, whereby, given a first height (h1) above the plane and a second height (h2) above the first height, a necessary and sufficient condition for said each cell to be in an occupied state is to be matched by a projection of a hit point located above the first height, and a necessary condition for said each cell to be in a free state is to be crossed by a projection of an overhanging ray that has dropped below the second height when passing over said each cell. Eventually, a vehicle trajectory is determined based on the grid obtained for said each sensor and the trajectory is forwarded to a drive-by-wire system of the automated vehicle. The invention is further directed to related systems and computer program products.
The invention is notably directed to a control system for steering an automated vehicle in a designated area, where the automated vehicle comprises a drive-by-wire (DbW) system. The control system includes a set of perception sensors (e.g., lidars, cameras, as well as radars, sonars, GPS, and inertial measurement units), which are arranged in a designated area. The control system further includes a control unit, which is in communication with the perception sensors and the DbW system, and which comprises two processing systems, i.e., a first processing system and a second processing system, which are in communication with each other. The first processing system is configured to form a main perception based on signals from each of the perception sensors of the set, estimate states of the vehicle based on feedback signals from the DbW system, and compute trajectories for the automated vehicle based on the main perception formed and the estimated states. The second processing system is configured to form an auxiliary perception based on signals from only a subset of the perception sensors, validate the computed trajectories based on the auxiliary perception formed, and cause the control unit to forward the validated trajectories to the DbW system of the automated vehicle. This way, the vehicle can be remotely steered through the DbW system based on the validated trajectories forwarded to the DbW system. In other words, distinct perceptions are formed from overlapping sets of sensors, whereby one of the perceptions formed is used to validate trajectories obtained from the other. This requires less computational efforts, inasmuch as less signals (and therefore less information) are required to form the auxiliary perception. However, doing so is more likely to allow inconsistencies to be detected, thanks to the heterogeneity of sensor signals considered in input to the main and auxiliary perceptions. The invention is further directed to related methods and computer program products.
The invention is notably directed to a method of driving an automated vehicle (10) comprising a drive-by-wire (DbW) system (300) with electromechanical actuators. The method is performed by a validation unit (220), which is connected to a motion planning unit (106). The validation unit and the motion planning unit may form part of the vehicle, making it an autonomous vehicle. In variants, the validation unit and the motion planning unit form part of a central control unit, which, e.g., remotely steers the vehicle in a designated area. The method and revolves around receiving (S10) provisional commands and accordingly triggering (S70-S90) an actuation sequence. The provisional commands are received (S10) from the motion planning unit (106). The provisional commands contain provisional instructions with respective execution times. The provisional commands are designed to be executed by respective ones of the electromechanical actuators to cause the vehicle (10) to follow a drivable trajectory. The actuation sequence is triggered (S70-S90) by generating (S70) effective commands based on the provisional commands received and timely sending (S80) the effective commands generated to the electromechanical actuators, whereby an effective command containing an effective instruction is repeatedly generated (S70) for and sent (S80) to each actuator of said electromechanical actuators. Each effective command of at least some of the effective commands sent to said each actuator is generated (S70) by selecting (S76) provisional commands and accordingly determining (S77) the effective instruction of each effective command. That is, two or more provisional commands are selected (S76) among the provisional commands received in respect of each actuator, in accordance with an effective time point, the latter corresponding to a current time point corrected to compensate for an actuator delay of said each actuator. The effective instruction of each effective command is then determined (S77) based on provisional instructions of the two or more provisional commands selected and their respective execution times. The invention is further directed to related systems and computer program products.
The invention is notably directed to an autonomous vehicle, e.g., an autonomous or semi-autonomous vehicle such as a self-driving car. The autonomous vehicle comprises a drive-by-wire (DbW) system (300), a set of perception sensors 21-24, such as lidars and cameras, and two processing systems, i.e., a first processing system (100) and a second processing system (200). The first processing system is configured to form a main perception based on signals from each of the perception sensors of the set, estimate states of the vehicle based on feedback signals from the DbW system, and compute trajectories for the autonomous vehicle based on the perception formed and the estimated states. The second processing system is configured to form an auxiliary perception based on signals from only a subset of the perception sensors, validate the computed trajectories based on the auxiliary perception formed, and cause to forward the validated trajectories to the DbW system. In other words, distinct perceptions are formed from overlapping sets of sensors, whereby one of the perceptions formed is used to validate trajectories obtained from the other. This requires less computational efforts, inasmuch as less signals (and therefore less information) are required to form the auxiliary perception. However, doing so is more likely to allow inconsistencies to be detected, thanks to the heterogeneity of sensor signals considered in input to the main and auxiliary perceptions. The invention is further directed to related methods and computer program products.
The present invention is directed to computer-implemented method for controlling an autonomous or semi-autonomous vehicle. A vehicle model is provided and information describing a roadway (301) is obtained. This information is transformed in a Frenet-Serret frame, which defines a curvilinear coordinate space. Then, in the curvilinear coordinate space, a plurality of line segments (306, 307) are defined (3) along the roadway (301), at locations spaced longitudinally along a reference line defining the Frenet-Serret frame. The line segments have respective lengths that extends, each, perpendicularly to the reference line. Next, based on the defined line segments, a space-time corridor (327, 327″, 326″) is determined (5) to obtain a time-dependent space available for the vehicle. Bounds for the vehicle within said time-dependent space are subsequently obtained (6). The bounds define a set of constraints that delimit a plurality of convex space-time objects along the reference line. Said objects approximate the time-dependent space. Then, based on the obtained set of constraints and the provided vehicle model, the method provides (7) a motion trajectory of the vehicle through the plurality of convex space-time objects. This motion trajectory is optimized using a nonlinear programming solver. Finally, the motion trajectory is transformed (8) from the curvilinear coordinate space to a Euclidean coordinate space, to control the vehicle based on the transformed motion trajectory. The present invention further concerns related systems and computer program products.
The invention is notably directed to a computer-implemented method for automatically charging an electric vehicle via an end effector (10) of a robotic arm (40) of an automated vehicle charging robot. The end effector is assumed to be structured so as to be able to connect to a charge port (220) of a vehicle. In addition, the automated vehicle charging robot further includes a camera system (102) having depth sensing capability. The method comprises the following steps. First, a reference position of a reference feature (210) of the vehicle is estimated thanks to the camera system. Next, a pose of the charge port of the vehicle is determined based on the estimated reference position. The robotic arm is subsequently instructed to actuate the end effector, based on the determined pose of the charge port, to connect the end effector to the charge port with a view to charging the vehicle. The reference position is estimated as follows. Both a 2D image and a depth image of a surface portion of the vehicle are obtained. This surface portion includes the reference feature, i.e., the feature of interest. Contour points of the reference feature are then extracted from the 2D image obtained. The 3D coordinates of the extracted contour points are subsequently reconstructed based on the depth image obtained. A geometric object (such a 2D plane) is then matched to the reconstructed 3D coordinates, e.g., by fitting the geometric object to the reconstructed 3D coordinates. Eventually, the reference position of the reference feature is determined based on the matched geometric object. The invention is further directed to related automated vehicle charging robots and computer program products.
B60L 53/37 - Means for automatic or assisted adjustment of the relative position of charging devices and vehicles using optical position determination, e.g. using cameras
13.
END EFFECTOR OF AUTOMATED VEHICLE CHARGING ROBOT FOR AUTOMATICALLY OPENING DOORS OF CHARGE PORTS OF ELECTRIC VEHICLES AND PLUGGING CHARGING CABLES
The invention is notably directed to end effector (10, 10a) for an automated vehicle charging robot (1). The end effector (10, 10a) comprises: a connecting module (100), which is delimited by a reference plane (P) and is designed to enable a connection of the end effector (10, 10a) to a robotic arm (40) of the charging robot (1) on a first side of the reference plane (P); an electrical connector (106, 108) including a body (108) and a plug (106), the plug designed to connect to a charge port (220) and arranged at an end of the body (108), wherein the body (108) extends from the connecting module (100) to the plug (106) on a second side of the reference plane (P), the second side opposite to said first side, along an extension direction (De) that is transverse to the reference plane (P); and an actuator (114, 115) that protrudes from said body (108), transversely to said extension direction (De), the actuator (114, 115) designed to actuate a door (210) of the vehicle charge port (220). The invention is further directed to: a functionalized robotic arm (40), which includes such an end effector; an automated vehicle charging system (1), which includes such a robotic arm; and a method of electrically charging an electrical vehicle using such a functionalized robotic arm.
B60L 53/35 - Means for automatic or assisted adjustment of the relative position of charging devices and vehicles
B60L 53/37 - Means for automatic or assisted adjustment of the relative position of charging devices and vehicles using optical position determination, e.g. using cameras
ref. Such control signals can be used for controlling (S40) a speed of the vehicle along each of said local sections of the route segment. The invention is further directed to related systems, vehicles, and computer program products.
The invention is notably directed to computer-implemented method of planning motion of a vehicle. The method comprises receiving (S20) real-time signals as to positions of N traffic participants. At each time step of multiple time steps, the method plans (S50) motion for the vehicle by computing (S30) states of each of the N traffic participants according to the signals received (S20). Said states include current states, which are estimated for each of the N traffic participants, as well as future states of each of the participants, wherein the future states are predicted over a prediction horizon T. This is achieved using an interaction-aware model of the N traffic participants. This model is designed to cause the method to recursively compute (S32-S38), at said each time step, the states of each of the N traffic participants according to a hierarchical list. The N traffic participants are ordered in the list from a most determinative one to a least determinative one of the N traffic participants. As a result, the states of the η-th participant in the list are computed based on the states of each of the η−1 participants in the list, ∀η∈[2, . . . , N]. This model is further designed to cause the method to update and sort (S40) the hierarchical list based on rules of the road, wherein the rules are evaluated based on the states of each of the N traffic participants as computed at said each time step. The invention is further directed to related computerized systems, vehicles, and computer program products.
A method for steering a vehicle along a path in a driveway and around obstacles between a starting position into a target position, comprises the steps of determining the vehicle dimensions, steering and driving capabilities, carrying out a path optimization step to evaluate, based on a predetermined cost function, the least costly path between the starting position and the target position avoiding any collisions with obstacles. The method further comprises the further step of applying a path improver step, smoothening the trajectory obtained by the path optimization method by means of numerical optimization while fulfilling dynamical constraints on acceleration and steering rate of the vehicle through planning lateral and longitudinal movement of the vehicle in a joint optimization problem or by means of separate optimization problems.
B60W 40/12 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to parameters of the vehicle itself
G08G 1/0967 - Systems involving transmission of highway information, e.g. weather, speed limits
G08G 1/0968 - Systems involving transmission of navigation instructions to the vehicle
17.
MODEL-BASED PREDICTIVE CONTROL OF AN ELECTRIC VEHICLE
Battpminpp) describes how long the electric vehicle (1) re-quires to travel over the prediction horizon according to the calculated longitudinal trajectory, while the minimum travel duration (tmin) describes a minimum time period which the electric vehicle (1) requires to travel over the prediction horizon.
B60L 58/12 - Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries responding to state of charge [SoC]
18.
METHOD AND SYSTEM FOR CONTROLLING AUTONOMOUS OR SEMI-AUTONOMOUS VEHICLE
The present invention is directed to computer-implemented method for controlling an autonomous or semi-autonomous vehicle. A vehicle model is provided and information describing a roadway is obtained. This information is transformed in a Frenet-Serret frame, which defines a curvilinear coordinate space. Then, in the curvilinear coordinate space, a plurality of line segments are defined along the roadway, at locations spaced longitudinally along a reference line defining the Frenet-Serret frame. The line segments have respective lengths that extends, each, perpendicularly to the reference line. Next, based on the defined line segments, a space-time corridor is determined to obtain a time-dependent space available for the vehicle. Bounds for the vehicle within said time-dependent space are subsequently obtained. The bounds define a set of constraints that delimit a plurality of convex space-time objects along the reference line. Said objects approximate the time-dependent space. Then, based on the obtained set of constraints and the provided vehicle model, the method provides a motion trajectory of the vehicle through the plurality of convex space-time objects. This motion trajectory is optimized using a nonlinear programming solver. Finally, the motion trajectory is transformed from the curvilinear coordinate space to a Euclidean coordinate space, to control the vehicle based on the transformed motion trajectory. The present invention further concerns related systems and computer program products.
VrefVrefVrefref.Such control signals can be used for controlling a speed of the vehicle along each of said local sections of the route segment. The invention is further directed to related systems, vehicles, and computer program products.
N NNTNNNηη NN traffic participants as computed at said each time step. The invention is further directed to related computerized systems, vehicles, and computer program products.
A method for steering a vehicle along a path in a driveway and around obstacles between a starting position into a target position, comprises the steps of determining the vehicle dimensions, steering and driving capabilities, carrying out a path optimization step to evaluate, based on a predetermined cost function, the least costly path between the starting position and the target position avoiding any collisions with obstacles. The method further comprises the further step of applying a path improver step, smoothening the trajectory obtained by the path optimization method by means of numerical optimization while fulfilling dynamical constraints on acceleration and steering rate of the vehicle through planning lateral and longitudinal movement of the vehicle in a joint optimization problem or by means of separate optimization problems.
B60W 40/12 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to parameters of the vehicle itself
G08G 1/0967 - Systems involving transmission of highway information, e.g. weather, speed limits
G08G 1/0968 - Systems involving transmission of navigation instructions to the vehicle
A method for steering a vehicle (12) along a path (400) in a driveway (50) and around obstacles (31, 32, 33, 34; 14) between a starting position (11) into a target position (12'), comprises the steps of determining the vehicle (12) dimensions, steering and driving capabilities, carrying out a path optimization step to evaluate, based on a predetermined cost function, the least costly path (400) between the starting position (11) and the target position (12') avoiding any collisions with obstacles (31, 32, 33, 34). The method further comprises the further step of applying a path improver step, smoothening the trajectory obtained by the path optimization method by means of numerical optimization while fulfilling dynamical constraints on acceleration and steering rate of the vehicle (12) through planning lateral and longitudinal movement of the vehicle in a joint optimization problem or by means of separate optimization problems.
