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.

Abstract: Abrasive devices suitable for use in cylinder style floor cleaning machines for the purpose of deep cleaning, restoring, honing and/or polishing are described. The abrasive devices include an elongated body and abrasive structures extending, at least in part, radially outward from an outwardly facing body surface, and relative to a rotational axis of the elongated body.

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.

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.

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.

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.

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.

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.

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.

Abstract: Embodiments disclosed herein enable a user to generate an audio-visual project. Certain embodiments enable a user to use one of a plurality of predefined templates to generate a project easily and quickly. Other embodiments enable a user to generate a custom project that gives more control to the user, compared to if the user selected one of the predefined templates. Each project includes one or more segments, which may be specified by a user directly, or may be specified by the template selected by the user. An effect is applied to each segment, wherein the effect specifies how many video and audio slots are included in the segment, if any, and can specify one or more other properties of the segment. Projects generated using embodiments disclosed herein can be saved and shared with other users.

Abstract: Embodiments disclosed herein enable a user to generate an audio-visual project. Certain embodiments enable a user to use one of a plurality of predefined templates to generate a project easily and quickly. Other embodiments enable a user to generate a custom project that gives more control to the user, compared to if the user selected one of the predefined templates. Each project includes one or more segments, which may be specified by a user directly, or may be specified by the template selected by the user. An effect is applied to each segment, wherein the effect specifies how many video and audio slots are included in the segment, if any, and can specify one or more other properties of the segment. Projects generated using embodiments disclosed herein can be saved and shared with other users.

Abstract: Embodiments disclosed herein enable a user to generate an audio-visual project. Certain embodiments enable a user to use one of a plurality of predefined templates to generate a project easily and quickly. Other embodiments enable a user to generate a custom project that gives more control to the user, compared to if the user selected one of the predefined templates. Each project includes one or more segments, which may be specified by a user directly, or may be specified by the template selected by the user. An effect is applied to each segment, wherein the effect specifies how many video and audio slots are included in the segment, if any, and can specify one or more other properties of the segment. Projects generated using embodiments disclosed herein can be saved and shared with other users.

Abstract: A graphical user interface is implemented as a human interface device which can directly sense where on a domed screen a user is pointing. The human interface device can be an optical pointing device which emits a beam of light, preferably produced using a laser, which can be tracked by a camera appropriately located inside the dome. As an alternative, the human interface device can be a hand held device capable of tracking position and orientation. Data produced by the human interface device is then detected and mapped to the location for a corresponding cursor.

Abstract: Embodiments disclosed herein enable a user to generate an audio-visual project. Certain embodiments enable a user to use one of a plurality of predefined templates to generate a project easily and quickly. Other embodiments enable a user to generate a custom project that gives more control to the user, compared to if the user selected one of the predefined templates. Each project includes one or more segments, which may be specified by a user directly, or may be specified by the template selected by the user. An effect is applied to each segment, wherein the effect specifies how many video and audio slots are included in the segment, if any, and can specify one or more other properties of the segment. Projects generated using embodiments disclosed herein can be saved and shared with other users.

Abstract: A graphical user interface is implemented as a human interface device which can directly sense where on a domed screen a user is pointing. The human interface device can be an optical pointing device which emits a beam of light, preferably produced using a laser, which can be tracked by a camera appropriately located inside the dome. As an alternative, the human interface device can be a hand held device capable of tracking position and orientation. Data produced by the human interface device is then detected and mapped to the location for a corresponding cursor.