Boston Dynamics, Inc.

Adam Komoroski

Christopher Stathis

Alex Yu Khripin

Eric Cary Whitman

Gina Christine Fay

Matthew David Malchano

Max Bajracharya

Brian Yamauchi

Matthew Jacob Klingensmith

Robert Eugene Paolini

Dion Gonano

A computer-implemented method executed by data processing hardware of a robot causes the data processing hardware to perform operations. The operations include receiving a sensor pointing command that commands the robot to use a sensor to capture sensor data of a location in an environment of the robot. The sensor is disposed on the robot. The operations include determining, based on an orientation of the sensor relative to the location, a direction for pointing the sensor toward the location, and an alignment pose of the robot to cause the sensor to point in the direction toward the location. The operations include commanding the robot to move from a current pose to the alignment pose. After the robot moves to the alignment pose and the sensor is pointing in the direction toward the location, the operations include commanding the sensor to capture the sensor data of the location in the environment.

Autonomous and teleoperated sensor pointing on a mobile robot

Methods and apparatus for navigating a robot along a route through an environment, the route being associated with a mission, are provided. The method comprises identifying, based on sensor data received by one or more sensors of the robot, a set of potential obstacles in the environment, determining, based at least in part on stored data indicating a set of footfall locations of the robot during a previous execution of the mission, that at least one of the potential obstacles in the set is an obstacle, and navigating the robot to avoid stepping on the obstacle.

Ground clutter avoidance for a mobile robot

A method of constrained mobility mapping includes receiving from at least one sensor of a robot at least one original set of sensor data and a current set of sensor data. Here, each of the at least one original set of sensor data and the current set of sensor data corresponds to an environment about the robot. The method further includes generating a voxel map including a plurality of voxels based on the at least one original set of sensor data. The plurality of voxels includes at least one ground voxel and at least one obstacle voxel. The method also includes generating a spherical depth map based on the current set of sensor data and determining that a change has occurred to an obstacle represented by the voxel map based on a comparison between the voxel map and the spherical depth map. The method additional includes updating the voxel map to reflect the change to the obstacle.

Constrained mobility mapping

A method of identifying stairs from footfalls includes receiving a plurality of footfall locations of a robot traversing an environment. Each respective footfall location indicates a location where a leg of the robot contacted a support surface. The method also includes determining a plurality of candidate footfall location pairs based on the plurality of footfall locations. The candidate footfall location pair includes a first and a second candidate footfall location. The method further includes clustering the first candidate footfall location into a first cluster group based on a height of the first candidate footfall location and clustering the second candidate footfall location into a second cluster group based on a height of the second candidate footfall location. The method additionally includes generating a stair model by representing each of the cluster groups as a corresponding stair and delineating each stair based on a respective midpoint between each adjacent cluster group.

Identifying stairs from footfalls

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Waltham, MA, United States of America

Adam Komoroski