Abstract:
Example systems and methods are disclosed for implementing vehicle operation limits to prevent vehicle load failure during vehicle teleoperation. The method may include receiving sensor data from sensors on a vehicle that carries a load. The vehicle may be controlled by a remote control system. The load weight and dimensions may be determined based on the sensor data. In order to prevent a vehicle load failure, a forward velocity limit and an angular velocity limit may be calculated. Vehicle load failures may include the vehicle tipping over, the load tipping over, the load sliding off of the vehicle, or collisions. The vehicle carrying the load may be restricted from exceeding the forward velocity limit and/or the angular velocity limit during vehicle operation. The remote control system may display a user interface indicating to a remote operator the forward velocity limit and the angular velocity limit.
Abstract:
Example systems and methods are disclosed for implementing vehicle operation limits to prevent vehicle load failure during vehicle teleoperation. The method may include receiving sensor data from sensors on a vehicle that carries a load. The vehicle may be controlled by a remote control system. The load weight and dimensions may be determined based on the sensor data. In order to prevent a vehicle load failure, a forward velocity limit and an angular velocity limit may be calculated. Vehicle load failures may include the vehicle tipping over, the load tipping over, the load sliding off of the vehicle, or collisions. The vehicle carrying the load may be restricted from exceeding the forward velocity limit and/or the angular velocity limit during vehicle operation. The remote control system may display a user interface indicating to a remote operator the forward velocity limit and the angular velocity limit.
Abstract:
Methods and systems for distributing remote assistance to facilitate robotic object manipulation are provided herein. Regions of a model of objects in an environment of a robotic manipulator may be determined, where each region corresponds to a different subset of objects with which the robotic manipulator is configured to perform a respective task. Certain tasks may be identified, and a priority queue of requests for remote assistance associated with the identified tasks may be determined based on expected times at which the robotic manipulator will perform the identified tasks. At least one remote assistor device may then be requested, according to the priority queue, to provide remote assistance with the identified tasks. The robotic manipulator may then be caused to perform the identified tasks based on responses to the requesting, received from the at least one remote assistor device, that indicate how to perform the identified tasks.
Abstract:
Systems and methods are provided for generating maps with semantic labels. A computing device can determine a first map that includes features located at first positions and semantic labels located at semantic positions, and determine a second map that includes at least some of the features located at second positions. The computing device can identify a first region with fixed features located at first positions and corresponding equivalent second positions. The computing device can identify a second region with moved features located at first positions and corresponding non-equivalent second positions. The computing device can determine one or more transformations between first positions and second positions. The computing device can assign the semantic labels to the second map at second semantic positions, where the second semantic positions are the same in the first region, and where the second semantic positions in the second region are based on the transformation(s).
Abstract:
Methods and systems for distributing remote assistance to facilitate robotic object manipulation are provided herein. Regions of a model of objects in an environment of a robotic manipulator may be determined, where each region corresponds to a different subset of objects with which the robotic manipulator is configured to perform a respective task. Certain tasks may be identified, and a priority queue of requests for remote assistance associated with the identified tasks may be determined based on expected times at which the robotic manipulator will perform the identified tasks. At least one remote assistor device may then be requested, according to the priority queue, to provide remote assistance with the identified tasks. The robotic manipulator may then be caused to perform the identified tasks based on responses to the requesting, received from the at least one remote assistor device, that indicate how to perform the identified tasks.
Abstract:
Methods and systems for distributing remote assistance to facilitate robotic object manipulation are provided herein. Regions of a model of objects in an environment of a robotic manipulator may be determined, where each region corresponds to a different subset of objects with which the robotic manipulator is configured to perform a respective task. Certain tasks may be identified, and a priority queue of requests for remote assistance associated with the identified tasks may be determined based on expected times at which the robotic manipulator will perform the identified tasks. At least one remote assistor device may then be requested, according to the priority queue, to provide remote assistance with the identified tasks. The robotic manipulator may then be caused to perform the identified tasks based on responses to the requesting, received from the at least one remote assistor device, that indicate how to perform the identified tasks.