Abstract: Obstacle detection for a mobile automation apparatus is provided. The mobile automation apparatus includes a structured light camera positioned on a support structure to detect at least a top of a shopping cart in a region adjacent to the mobile automation apparatus. The mobile automation apparatus can include other structured light cameras. Furthermore, one or more ultrasound arrays are used as secondary obstacle detector such that when the one or more ultrasound arrays detect an object, and at least one structured light camera simultaneously does not detect the object, an obstacle avoidance protocol is implemented.

Abstract: A control method in a mobile automation apparatus includes: storing a plurality of parametric path definition identifiers and respective corresponding sub-region identifiers identifying sub-regions in a facility; receiving a task command containing (i) a task identifier, and (ii) a target one of the sub-region identifiers identifying a target one of the sub-regions; retrieving a selected one of the parametric path definition identifiers corresponding to the target sub-region identifier; obtaining a selected one of a plurality of parametric path definitions—including a shape parameter and a reference parameter name—corresponding to the selected parametric path definition identifier; obtaining a reference parameter value, and generating a sequence of mobile automation apparatus poses according to the parametric path definition; each pose corresponding to a location in the facility; and controlling a locomotive assembly of the mobile automation apparatus to traverse the target sub-region according to the sequenc

Abstract: A device and method for multimodal localization and mapping for a mobile automation apparatus is provided. Features are extracted from images acquired by a ceiling-facing image device of the mobile automation apparatus in an environment, and stored in association with estimated positions of the mobile automation apparatus in the environment as determined from one or more sensors, as well as in association with features extracted from depth data acquired from a depth-sensing device, for example as map data. The map data is later used by the mobile automation apparatus to navigate the environment based, at least in part, on further images acquired by the ceiling-facing image device.

Abstract: A control method in a mobile automation apparatus includes: storing a plurality of parametric path definition identifiers and respective corresponding sub-region identifiers identifying sub-regions in a facility; receiving a task command containing (i) a task identifier, and (ii) a target one of the sub-region identifiers identifying a target one of the sub-regions; retrieving a selected one of the parametric path definition identifiers corresponding to the target sub-region identifier; obtaining a selected one of a plurality of parametric path definitions—including a shape parameter and a reference parameter name—corresponding to the selected parametric path definition identifier; obtaining a reference parameter value, and generating a sequence of mobile automation apparatus poses according to the parametric path definition; each pose corresponding to a location in the facility; and controlling a locomotive assembly of the mobile automation apparatus to traverse the target sub-region according to the sequenc

Abstract: Obstacle detection for a mobile automation apparatus is provided. The mobile automation apparatus includes a structured light camera positioned on a support structure to detect at least a top of a shopping cart in a region adjacent to the mobile automation apparatus. The mobile automation apparatus can include other structured light cameras. Furthermore, one or more ultrasound arrays are used as secondary obstacle detector such that when the one or more ultrasound arrays detect an object, and at least one structured light camera simultaneously does not detect the object, an obstacle avoidance protocol is implemented.

Abstract: A device and method for multimodal localization and mapping for a mobile automation apparatus is provided. Features are extracted from images acquired by a ceiling-facing image device of the mobile automation apparatus in an environment, and stored in association with estimated positions of the mobile automation apparatus in the environment as determined from one or more proprioceptive sensors, as well as in association with features extracted from depth data acquired from a depth-sensing device, for example as map data. The map data is later used by the mobile automation apparatus to navigate the environment based, at least in part, on further images acquired by the ceiling-facing image device.