-
公开(公告)号:US10606269B2
公开(公告)日:2020-03-31
申请号:US15847108
申请日:2017-12-19
Applicant: X Development LLC
Inventor: David Millard , Mikael Persson
Abstract: Systems, methods, devices, and techniques for planning travel of an autonomous robot. A system identifies one or more obstacles that are located in proximity of at least a portion of a planned route for the autonomous robot. For each obstacle, the system: (i) determines a semantic class of the obstacle, including selecting the semantic class from a library that defines a set of multiple possible semantic classes for obstacles, and (ii) selects a planning policy for the obstacle that corresponds to the semantic class of the obstacle. The system can generate a trajectory along the at least the portion of the planned route using the selected planning policies. The robot can then initiate travel according to the trajectory.
-
公开(公告)号:US20210080970A1
公开(公告)日:2021-03-18
申请号:US16580714
申请日:2019-09-24
Applicant: X Development LLC
Inventor: Ammar Husain , Mikael Persson
Abstract: Implementations set forth herein relate to a robot that employs a stereo camera and LIDAR for generating point cloud data while the robot is traversing an area. The point cloud data can characterize spaces within the area as occupied, unoccupied, or uncategorized. For instance, an uncategorized space can refer to a point in three-dimensional (3D) space where occupancy of the space is unknown and/or where no observation has been made by the robot—such as in circumstances where a blind spot is located at or near a base of the robot. In order to efficiently traverse certain areas, the robot can estimate resource costs of either sweeping the stereo camera indiscriminately between spaces and/or specifically focusing the stereo camera on uncategorized space(s) during the route. Based on such resource cost estimations, the robot can adaptively maneuver the stereo camera during routes while also minimizing resource consumption by the robot.
-
公开(公告)号:US20200293044A1
公开(公告)日:2020-09-17
申请号:US16832837
申请日:2020-03-27
Applicant: X Development LLC
Inventor: David Millard , Mikael Persson
Abstract: Systems, methods, devices, and techniques for planning travel of an autonomous robot. A system identifies one or more obstacles that are located in proximity of at least a portion of a planned route for the autonomous robot. For each obstacle, the system: (i) determines a semantic class of the obstacle, including selecting the semantic class from a library that defines a set of multiple possible semantic classes for obstacles, and (ii) selects a planning policy for the obstacle that corresponds to the semantic class of the obstacle. The system can generate a trajectory along the at least the portion of the planned route using the selected planning policies. The robot can then initiate travel according to the trajectory.
-
公开(公告)号:US20230084774A1
公开(公告)日:2023-03-16
申请号:US17932271
申请日:2022-09-14
Applicant: X Development LLC
Inventor: Ammar Husain , Mikael Persson
Abstract: A method includes determining, for a robotic device that comprises a perception system, a robot planner state representing at least one future path for the robotic device in an environment. The method also includes determining a perception system trajectory by inputting at least the robot planner state into a machine learning model trained based on training data comprising at least a plurality of robot planner states corresponding to a plurality of operator-directed perception system trajectories. The method further includes controlling, by the robotic device, the perception system to move through the determined perception system trajectory.
-
公开(公告)号:US20220365532A1
公开(公告)日:2022-11-17
申请号:US17814738
申请日:2022-07-25
Applicant: X Development LLC
Inventor: David Millard , Mikael Persson
Abstract: Systems, methods, devices, and techniques for planning travel of an autonomous robot. A system identifies one or more obstacles that are located in proximity of at least a portion of a planned route for the autonomous robot. For each obstacle, the system: (i) determines a semantic class of the obstacle, including selecting the semantic class from a library that defines a set of multiple possible semantic classes for obstacles, and (ii) selects a planning policy for the obstacle that corresponds to the semantic class of the obstacle. The system can generate a trajectory along the at least the portion of the planned route using the selected planning policies. The robot can then initiate travel according to the trajectory.
-
公开(公告)号:US11429103B2
公开(公告)日:2022-08-30
申请号:US16832837
申请日:2020-03-27
Applicant: X Development LLC
Inventor: David Millard , Mikael Persson
Abstract: Systems, methods, devices, and techniques for planning travel of an autonomous robot. A system identifies one or more obstacles that are located in proximity of at least a portion of a planned route for the autonomous robot. For each obstacle, the system: (i) determines a semantic class of the obstacle, including selecting the semantic class from a library that defines a set of multiple possible semantic classes for obstacles, and (ii) selects a planning policy for the obstacle that corresponds to the semantic class of the obstacle. The system can generate a trajectory along the at least the portion of the planned route using the selected planning policies. The robot can then initiate travel according to the trajectory.
-
公开(公告)号:US20190187703A1
公开(公告)日:2019-06-20
申请号:US15847108
申请日:2017-12-19
Applicant: X Development LLC
Inventor: David Millard , Mikael Persson
CPC classification number: G05D1/0088 , B25J9/0003 , B25J9/1666 , G01C21/00 , G05D1/0214 , G05D1/0217 , G05D1/0221 , G05D1/0223 , G05D1/024 , G05D1/0246 , G05D1/0274 , G06K9/00664 , Y10S901/01 , Y10S901/47
Abstract: Systems, methods, devices, and techniques for planning travel of an autonomous robot. A system identifies one or more obstacles that are located in proximity of at least a portion of a planned route for the autonomous robot. For each obstacle, the system: (i) determines a semantic class of the obstacle, including selecting the semantic class from a library that defines a set of multiple possible semantic classes for obstacles, and (ii) selects a planning policy for the obstacle that corresponds to the semantic class of the obstacle. The system can generate a trajectory along the at least the portion of the planned route using the selected planning policies. The robot can then initiate travel according to the trajectory.
-
-
-
-
-
-