Abstract: An autonomous tray handling robotic system is disclosed. In various embodiments, data indicating a set of output stacks to be assembled is stored, each output stack including an associated set of trays each of a corresponding tray type. Operation of one or more robots is controlled, each robot being configured to grasp, move, and place one or more trays at a time, according to a plan, to iteratively pick trays from source stacks of trays and assemble the set of output stacks, including by building each output stack by successively placing on the output stack trays picked from one or more corresponding source stacks. Each of the robots comprises a robotic arm and a tray handling end effector configured to grasp, move, and place one or more trays without assistance from another robot.

Abstract: A multicamera image processing system is disclosed. In various embodiments, image data is received from each of a plurality of sensors associated with a workspace, the image data comprising for each sensor in the plurality of sensors one or both of visual image information and depth information. Image data from the plurality of sensors is merged to generate a merged point cloud data. Segmentation is performed based on visual image data from at least a subset of the sensors in the plurality of sensors to generate a segmentation result. One or both of the merged point cloud data and the segmentation result is/are used to generate a merged three dimensional and segmented view of the workspace.

Abstract: A kitting machine is disclosed. In various embodiments, the machine includes an actuator configured to move a surface or receptacle to a position associated with item retrieval; and a controller configured to control operation of the actuator to position an item in the position associated with item retrieval, in a manner that is synchronized at least in part with operation of a robotic retrieval device configured to retrieve the item from the position associated with item retrieval.

Abstract: A multicamera image processing system is disclosed. In various embodiments, image data is received from each of a plurality of sensors associated with a workspace, the image data comprising for each sensor in the plurality of sensors one or both of visual image information and depth information. Image data from the plurality of sensors is merged to generate a merged point cloud data. Segmentation is performed based on visual image data from at least a subset of the sensors in the plurality of sensors to generate a segmentation result. One or both of the merged point cloud data and the segmentation result is/are used to generate a merged three dimensional and segmented view of the workspace.

Abstract: The present application discloses a method, system, and computer system for arranging a set of objects for loading to a transport container. The method includes (i) receiving an indication of the set of objects to be loaded into the transport container for transport from a source location to a destination location, (ii) determining, based at least in part on object information corresponding to the set of objects and resources available to load the set of objects, an arrangement of the set of objects loaded into the transport container that satisfies a weight distribution criteria, and (iii) providing the arrangement as an output to be used in connection with loading the set of objects to the transport container.

Abstract: The present application discloses a method, system, and computer system for partitioning a set of objects among a set of transport containers. The method includes (i) receiving an indication of the set of objects to be loaded into the set of transport containers, (ii) determining, based at least in part on object information corresponding to the set of objects and resources available to load the set of objects, an plan to partition the set of objects across the set of transport containers, the plan including an indication of a subset of the objects allocated to a corresponding subset of the containers, and (iii) providing the plan as an output to be used in connection with loading various subsets of objects to corresponding subsets of containers.

Abstract: A robotic kitting machine is disclosed. In various embodiments, a robotic arm is used to move an item to a location in proximity to a slot into which the item is to be inserted. Force information generated by a force sensor is received via a communication interface. The force sensor information is used to align a structure comprising the item with a corresponding cavity comprising the slot, and the item is inserted into the slot.

Abstract: A multicamera image processing system is disclosed. In various embodiments, image data is received from each of a plurality of sensors associated with a workspace, the image data comprising for each sensor in the plurality of sensors one or both of visual image information and depth information. Image data from the plurality of sensors is merged to generate a merged point cloud data. Segmentation is performed based on visual image data from at least a subset of the sensors in the plurality of sensors to generate a segmentation result. One or both of the merged point cloud data and the segmentation result is/are used to generate a merged three dimensional and segmented view of the workspace.

Abstract: A robotic system is disclosed to control multiple robots to cooperatively pick and place objects. In various embodiments, the robotic system includes a first robotic arm having a first end effector; a second robotic arm having a second end effector; and a control computer configured to use the first robotic arm and the second robotic arm to pick and place a plurality of objects, including by using the first robotic arm and the second robotic arm to work cooperatively to pick and place one or more of the objects.

Abstract: 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.

Abstract: A robotic system to control multiple robots to perform a task cooperatively is disclosed. A first robot determines to perform a task cooperatively with a second robot, moves independently to a first grasp position to grasp an object associated with the task, receives an indication that the second robot is prepared to perform the task cooperatively, and moves the object independently of the second robot in a leader mode along a trajectory determined by the first robot. The second robot assists the first robot in performing the task cooperatively, at least in part by moving independently to a second grasp position, grasping the object, and cooperating with the first robot to move the object, at least in part by operating in a follower mode of operation to maintain engagement with the object as the first robot moves the object along the trajectory.

Abstract: 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.

Abstract: A robotic system is disclosed. The system includes a memory that stores for each of a plurality of items a set of attribute values. The system includes a processor(s) that uses the attribute values to simulate the placement of items, including by determining, iteratively, for each next item a placement location at which to place the item on a simulated stack of items on the pallet, using the attribute values and a geometric model of where items have been simulated to have been placed to estimate a state of the stack after each of a subset of simulated placements, and using the estimated state to inform a next placement decision. The steps of determining for each next item a placement location and estimating the state of the stack until all of at least a subset of the plurality of items have been simulated as having been placed on the stack.

Abstract: A robotic system is disclosed. The system includes a memory that stores a machine learning-based model to provide a scoring function value for a candidate item placement on a pallet on which are plurality of items are to be stacked given a current state value of the pallet and a set of zero or more items placed previously. The system includes one or more processors that use the model to determine a corresponding score for each of a plurality of candidate placements for a next item to be placed and the current state value associated with the current state of the pallet and a set of zero or more items placed previously, select a selected placement based at least in part on the respective scores, control a robotic arm to place the next item according to the selected placement.

Abstract: A robotic system is disclosed. The system includes a memory configured to store estimated state information associated with a computer simulation of a robotic operation to stack a plurality of items on a pallet or other receptacle. The system includes one or more processors coupled to the communication interface and configured to perform the computer simulation. The computer simulation is performed at least in part by combining geometric model data based on idealized simulated robotic placement of each item with programmatically generated noise data. The programmatically generated noise data reflects an estimation of the effect that one or more sources of noise in a real-world physical workspace with which the computer simulation is associated would have on a real-world state of the plurality of items and/or the pallet or other receptacle if the plurality of items were stacked on the pallet or other receptacle as simulated in the computer simulation.

Abstract: A robotic system is disclosed. The system includes a communication interface that receives, from a sensor(s) deployed in a workspace, sensor data indicative of a current state of the workspace, the workspace comprising a pallet or other receptacle and a plurality of items stacked on or in the receptacle. The system includes one or more processors that control a robotic arm to place a first set of items on or in, or remove the first set of items from, the pallet or other receptacle, update a geometric model based on the first set of items placed on or in a receptacle, use the geometric model in combination with the sensor data to estimate a stack of one or more items on or in the receptacle, and use the estimated state to generate or update a plan to control the robotic arm to place a second set of items.

Abstract: A robotic system is disclosed. The system includes a communication interface configured to receive, from one or more sensors deployed in a workspace, sensor data indicative of a current state of the workspace, the workspace comprising a pallet or other receptacle and a plurality of items stacked on or in the receptacle. The system includes one or more processors that use a geometric model based at least in part on past item placements in combination with the sensor data to estimate a state of the pallet or other receptacle and one or more items stacked on or in the pallet or other receptacle, and use the estimated state to generate or update a plan to control a robotic arm to place a next item on or in, or remove a next item from, the pallet or other receptacle in a manner that avoids having the next item collide with any other item stacked on or in the pallet or other receptacle.

Abstract: A robotic system is disclosed. The system includes a memory configured to store for each of a plurality of items a set of attribute values representing one or more physical attributes of the item. The system includes one or more processors coupled to the communication interface and configured to use the attribute values as inputs to a physic engine configured to compute the stability of a simulated stack of items comprising at least a subset of the plurality of items.

Abstract: A robotic system is disclosed. The system includes a communication interface that receives, from one or more sensors deployed in a workspace, sensor data indicative of a current state of the workspace. The system includes one or more processors that use the sensor data to estimate a state of one or both of the pallet or other receptacle and the set of zero or more items stacked on or in the receptacle, and use the estimated state to generate or update a plan to control a robotic arm to place a next set of items on or in, or remove the next set of items from, the pallet or other receptacle, the plan comprising an ordered sequence of item placements or removals. The plan is generated or updated based at least in part by performing a bounded tree search in which a subset of possible ordered sequences is explored.

Abstract: A robotic line kitting system is disclosed. In various embodiments, data indicating for each of a plurality of operating zones comprising a workspace with which the robotic line kitting system is associated a corresponding safety state information is stored. The data is used to dynamically schedule and perform tasks associated with a higher level objective, including by operating the one or more robotic instrumentalities in one or more operating zones, if any, indicated by said data to currently be available to perform tasks using the one or more robotic instrumentalities and by not operating the one or more robotic instrumentalities in one or more operating zones, if any, indicated by said data to not currently be available to perform tasks using the one or more robotic instrumentalities.