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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.
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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.
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Patent Agency Ranking
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.
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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.
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公开(公告)号：US11650591B1
公开(公告)日：2023-05-16
申请号：US17325670
申请日：2021-05-20
Applicant: X Development LLC
Inventor： David Millard
CPC classification number: G05D1/0214 , G06N3/08 , G05B2219/39208 , G05D1/0231 , G05D1/0255 , G05D1/0257
Abstract: This specification describes trajectory planning for robotic devices. A robotic navigation system can obtain, for each of multiple time steps, data representing an environment of a robot at the time step. The system generates a series of occupancy maps for the multiple time steps, and uses the series of occupancy maps to determine occupancy predictions for one or more future time steps. Each occupancy prediction can identify predicted locations of obstacles in the environment of the robot at a different one of the future time steps. A planned trajectory can be determined for the robot using the occupancy predictions, and the robot initiates travel along the planned trajectory.
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公开(公告)号：US11016491B1
公开(公告)日：2021-05-25
申请号：US15881271
申请日：2018-01-26
Applicant: X Development LLC
Inventor： David Millard
Abstract: This specification describes trajectory planning for robotic devices. A robotic navigation system can obtain, for each of multiple time steps, data representing an environment of a robot at the time step. The system generates a series of occupancy maps for the multiple time steps, and uses the series of occupancy maps to determine occupancy predictions for one or more future time steps. Each occupancy prediction can identify predicted locations of obstacles in the environment of the robot at a different one of the future time steps. A planned trajectory can be determined for the robot using the occupancy predictions, and the robot initiates travel along the planned trajectory.
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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.
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