A task table for use in a robotic system comprising a robot mounted on a carriage configured to move the robot along a path is disclosed. The task table includes a substantially horizontal table surface, and one or more mounting arms to which the table surface is affixed at a first distal end and comprising, at a second distal end opposite the first distal end, one or more mounting structures, the one or more mounting arms having a length that allows the table surface to be mounted to the robot or the carriage at a distance from a base of the robot that enables the robot to reach a plurality of locations on the table surface each with a desired pose.

In one embodiment, a system is provided. The system includes a set of pallets to hold a set of parcels. The system also includes a conveyor system to move the set of pallets to and from a transportation pod. The system further includes a lift system to lift the set of pallets to different heights within the transportation pod. The system further includes a storage system to store a set of parcels. The system further includes a mechanical arm to move the set of parcels from the storage system to the set of pallets.

According to one embodiment, a cargo handling apparatus includes a hand, a robot arm, a transfer device, a measurement device, and a control device. The hand holds an article. The robot arm moves the hand. The transfer device is arranged with the robot arm, and transfers the article. The measurement device measures a position and a size of the article. The control device performs a first operation of transferring the article to the transfer device by using the hand and the robot arm, and a second operation of transferring the transferred article by using the transfer device. The control device determines whether or not the robot arm will interfere with the transfer device or a second article on the transfer device when performing the first operation for a first article. The control device controls a start timing of the first operation according to a determination result of the interference.

Techniques are disclosed to use a robotic arm to palletize or depalletize diverse items. In various embodiments, data associated with a plurality of items to be stacked on or in a destination location is received. A plan to stack the items on or in the destination location is generated based at least in part on the received data. The plan is implemented at least in part by controlling a robotic arm of the robot to pick up the items and stack them on or in the receptacle according to the plan, including by for each item: using one or more first order sensors to move the item to a first approximation of a destination position for that item at the destination location; and using one or more second order sensors to snug the item into a final position.

A method for retrieving content stored in a warehouse, the method may include: maintaining first content in boxes of a lowest shelf of a storage unit of the warehouse, while maintaining in boxes of higher shelves of the storage unit second content that is of less interest than the first content; accessing the boxes of the lowest shelf and providing the boxes to interfacing units, by a first robot; accessing the boxes of the higher shelves and providing the boxes to the interfacing units, by a second robot; wherein the first robot, when positioned at a lower position, is lower than a height of the lowest shelf, and wherein the second robot is higher than the height of the lowest shelf.

A method for automatically placing a to-be-packed object into a container that defines an accommodation space is provided. A processing unit obtains an object dimension data piece that indicates dimensions of the to-be-packed object, and obtains, through a camera unit that captures images of the to-be-packed object and the accommodation space, an unoccupied area related to the accommodation space. Based on the object dimension data piece and the unoccupied area, the processing unit determines whether the container is capable of accommodating the to-be-packed object.

Vision systems for robotic assemblies for handling cargo, for example, unloading cargo from a trailer, can determine the position of cargo based on shading topography. Shading topography imaging can be performed by using light sources arranged at different positions relative to the image capture device(s).

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.

Methods and apparatus for determining a grasp strategy to grasp an object with a gripper of a robotic device are described. The method comprises generating a set of grasp candidates to grasp a target object, wherein each of the grasp candidates includes information about a gripper placement relative to the target object, determining, for each of the grasp candidates in the set, a grasp quality, wherein the grasp quality is determined using a physical-interaction model including one or more forces between the target object and the gripper located at the gripper placement for the respective grasp candidate, selecting, based at least in part on the determined grasp qualities, one of the grasp candidates, and controlling the robotic device to attempt to grasp the target object using the selected grasp candidate.

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.