Abstract: Methods, robots, systems, and computer-readable media are provided for selectively uploading operational data generated by a robot to a remote computing system. In various implementations, a robot may classify a plurality of operational data points generated by the robot with a plurality of operational data types. The robot may also identify one or more attributes of a physical communication link between the robot and a remote computing system. Based on the one or more attributes of the physical communication link, the robot may identify a plurality of strategies for uploading operational data from the robot to the remote computing system. Each strategy may govern how operational data points of at least one of the plurality of operational data types is uploaded. The robot may then selectively upload the plurality of classified operational data points to the remote computing system pursuant to the plurality of strategies.

Abstract: Methods, robots, systems, and computer-readable media are provided for selectively uploading operational data generated by a robot to a remote computing system. In various implementations, a robot may classify a plurality of operational data points generated by the robot with a plurality of operational data types. The robot may also identify one or more attributes of a physical communication link between the robot and a remote computing system. Based on the one or more attributes of the physical communication link, the robot may identify a plurality of strategies for uploading operational data from the robot to the remote computing system. Each strategy may govern how operational data points of at least one of the plurality of operational data types is uploaded. The robot may then selectively upload the plurality of classified operational data points to the remote computing system pursuant to the plurality of strategies.

Abstract: Methods and systems for dynamically maintaining a map of robotic devices in an environment are provided herein. A map of robotic devices may be determined, where the map includes predicted future locations of at least some of the robotic devices. One or more robotic devices may then be caused to perform a task. During a performance of the task by the one or more robotic devices, task progress data may be received from the robotic devices, indicative of which of the task phases have been performed. Based on the data, the map may be updated to include a modification to the predicted future locations of at least some of the robotic devices. One or more robotic devices may then be caused to perform at least one other task in accordance with the updated map.

Abstract: Methods, apparatus, systems, and computer-readable media are provided for generating and using a spatio-temporal model that defines pose values for a plurality of objects in an environment and corresponding times associated with the pose values. Some implementations relate to using observations for one or more robots in an environment to generate a spatio-temporal model that defines pose values and corresponding times for multiple objects in the environment. In some of those implementations, the model is generated based on uncertainty measures associated with the pose values. Some implementations relate to utilizing a generated spatio-temporal model to determine the pose for each of one or more objects an environment at a target time. The pose for an object at a target time is determined based on one or more pose values for the object selected based on a corresponding measurement time, uncertainty measure, and/or source associated with the pose values.

Abstract: Methods and systems for dynamically maintaining a map of robotic devices in an environment are provided herein. A map of robotic devices may be determined, where the map includes predicted future locations of at least some of the robotic devices. One or more robotic devices may then be caused to perform a task. During a performance of the task by the one or more robotic devices, task progress data may be received from the robotic devices, indicative of which of the task phases have been performed. Based on the data, the map may be updated to include a modification to the predicted future locations of at least some of the robotic devices. One or more robotic devices may then be caused to perform at least one other task in accordance with the updated map.

Abstract: Methods and systems for dynamically maintaining a map of robotic devices in an environment are provided herein. A map of robotic devices may be determined, where the map includes predicted future locations of at least some of the robotic devices. One or more robotic devices may then be caused to perform a task. During a performance of the task by the one or more robotic devices, task progress data may be received from the robotic devices, indicative of which of the task phases have been performed. Based on the data, the map may be updated to include a modification to the predicted future locations of at least some of the robotic devices. One or more robotic devices may then be caused to perform at least one other task in accordance with the updated map.

Abstract: Methods, apparatus, systems, and computer-readable media are provided for selectively deploying robots to performing mapping based on added cost. In various implementations, a measure of interest in mapping an area of an environment may be determined. A cost associated with a robot performing a task may also be determined. Then, an added cost associated with the robot mapping the area of the environment while performing the task may be determined. The robot may be selectively deployed to map the area while performing the task in response to a determination that the measure of interest justifies the added cost.

Abstract: Methods, apparatus, systems, and computer-readable media are provided for generating and using a spatio-temporal model that defines pose values for a plurality of objects in an environment and corresponding times associated with the pose values. Some implementations relate to using observations for one or more robots in an environment to generate a spatio-temporal model that defines pose values and corresponding times for multiple objects in the environment. In some of those implementations, the model is generated based on uncertainty measures associated with the pose values. Some implementations relate to utilizing a generated spatio-temporal model to determine the pose for each of one or more objects an environment at a target time. The pose for an object at a target time is determined based on one or more pose values for the object selected based on a corresponding measurement time, uncertainty measure, and/or source associated with the pose values.

Abstract: Methods, apparatus, systems, and computer-readable media are provided for selectively deploying robots to performing mapping based on added cost. In various implementations, a measure of interest in mapping an area of an environment may be determined. A cost associated with a robot performing a task may also be determined. Then, an added cost associated with the robot mapping the area of the environment while performing the task may be determined. The robot may be selectively deployed to map the area while performing the task in response to a determination that the measure of interest justifies the added cost.

Abstract: Methods and systems for dynamically maintaining a map of robotic devices in an environment are provided herein. A map of robotic devices may be determined, where the map includes predicted future locations of at least some of the robotic devices. One or more robotic devices may then be caused to perform a task. During a performance of the task by the one or more robotic devices, task progress data may be received from the robotic devices, indicative of which of the task phases have been performed. Based on the data, the map may be updated to include a modification to the predicted future locations of at least some of the robotic devices. One or more robotic devices may then be caused to perform at least one other task in accordance with the updated map.

Abstract: The specification relates to framework for removing non-authored content documents from an authored-content database by recording a sequence of authorship data for at least one authored-content document over a period of time. The at least one authored-content document can be indexed in an authored-content database. The sequence of authorship data is analyzed to determine if the at least one authored-content document changed in a meaningful way beyond a set threshold. If the at least one authored-content document is changed beyond the set threshold, the at least one authored-content document is removed from the authored-content database.