Abstract: A perception mast for mobile robot is provided. The mobile robot comprises a mobile base, a turntable operatively coupled to the mobile base, the turntable configured to rotate about a first axis, an arm operatively coupled to a first location on the turntable, and the perception mast operatively coupled to a second location on the turntable, the perception mast configured to rotate about a second axis parallel to the first axis, wherein the perception mast includes disposed thereon, a first perception module and a second perception module arranged between the first imaging module and the turntable.

Abstract: A perception mast for mobile robot is provided. The mobile robot comprises a mobile base, a turntable operatively coupled to the mobile base, the turntable configured to rotate about a first axis, an arm operatively coupled to a first location on the turntable, and the perception mast operatively coupled to a second location on the turntable, the perception mast configured to rotate about a second axis parallel to the first axis, wherein the perception mast includes disposed thereon, a first perception module and a second perception module arranged between the first imaging module and the turntable.

Abstract: Methods and apparatus for determining a pose of an object sensed by a camera system of a mobile robot are described. The method includes acquiring, using the camera system, a first image of the object from a first perspective and a second image of the object from a second perspective, and determining, by a processor of the camera system, a pose of the object based, at least in part, on a first set of sparse features associated with the object detected in the first image and a second set of sparse features associated with the object detected in the second image.

Abstract: Methods and apparatus for automated calibration for a LIDAR system of a mobile robot are provided. The method comprises capturing a plurality of LIDAR measurements. The plurality of LIDAR measurements include a first set of LIDAR measurements as the mobile robot spins in a first direction at a first location, the first location being a first distance to a calibration target, and a second set of LIDAR measurements as the mobile robot spins in a second direction at a second location, the second location being a second distance to the calibration target, wherein the first direction and the second direction are different and the second distance is different than the first distance. The method further comprises processing the plurality of LIDAR measurements to determine calibration data, and generating alignment instructions for the LIDAR system based, at least in part, on the calibration data.

Abstract: Methods and apparatus for estimating a ceiling location of a container within which a mobile robot is configured to operate are provided. The method comprises sensing distance measurement data associated with the ceiling of the container using one or more distance sensors arranged on an end effector of a mobile robot, and determining a ceiling estimate of the container based on the distance measurement data.

Abstract: A kit includes a computing device configured to control motion of equipment for receiving one or more parcels in an environment of a mobile robot. The kit also includes a structure configured to couple to the equipment. The structure comprises an identifier configured to be sensed by a sensor of the mobile robot.

Abstract: Methods and apparatus for object detection and pick order determination for a robotic device are provided. Information about a plurality of two-dimensional (2D) object faces of the objects in the environment may be processed to determine whether each of the plurality of 2D object faces matches a prototype object of a set of prototype objects stored in a memory, wherein each of the prototype objects in the set represents a three-dimensional (3D) object. A model of 3D objects in the environment of the robotic device is generated using one or more of the prototype objects in the set of prototype objects that was determined to match one or more of the 2D object faces.

Abstract: Methods and apparatuses for detecting one or more objects (e.g., dropped objects) by a robotic device are described. The method comprises receiving a distance-based point cloud including a plurality of points in three dimensions, filtering the distance-based point cloud to remove points from the plurality of points based on at least one known surface in an environment of the robotic device to produce a filtered distance-based point cloud, clustering points in the filtered distance-based point cloud to produce a set of point clusters, and detecting one or more objects based, at least in part, on the set of point clusters.

Abstract: A perception mast for mobile robot is provided. The mobile robot comprises a mobile base, a turntable operatively coupled to the mobile base, the turntable configured to rotate about a first axis, an arm operatively coupled to a first location on the turntable, and the perception mast operatively coupled to a second location on the turntable, the perception mast configured to rotate about a second axis parallel to the first axis, wherein the perception mast includes disposed thereon, a first perception module and a second perception module arranged between the first imaging module and the turntable.

Abstract: An imaging apparatus includes a structural support rigidly coupled to a surface of a mobile robot and a plurality of perception modules, each of which is arranged on the structural support, has a different field of view, and includes a two-dimensional (2D) camera configured to capture a color image of an environment, a depth sensor configured to capture depth information of one or more objects in the environment, and at least one light source configured to provide illumination to the environment. The imaging apparatus further includes control circuitry configured to control a timing of operation of the 2D camera, the depth sensor, and the at least one light source included in each of the plurality of perception modules, and at least one computer processor configured to process the color image and the depth information to identify at least one characteristic of one or more objects in the environment.