A computing system including a processing circuit in communication with a robot and a camera having a field of view. The processing circuit obtains image information based on the objects in the field of view and a loading environment, the loading environment which includes loading areas, an object queue, and a buffer zone. The computing system is configured to use the obtained image information in motion planning operations for the retrieval and placement of objects from the object queue into the loading environment. Pallets provided within the loading environment (i.e., within the loading areas) are dedicated to receiving objects having corresponding object type identifiers. The computer system further uses the image information to determine the fill status of pallets existing within the loading environment, and whether new pallets need to be brought into the loading environment and/or swapped out with existing pallets to account for future planning and placement operations.

A system and method for estimating aspects of target objects and/or associated task implementations is disclosed.

A system and method for determining a misdetection of an object and subsequent response is disclosed. A robotic system may use a motion plan, which is derived based on an initial detection result of a package, to transfer the package from a start location to a task location. During implementation of the motion plan, the robotic system may obtain additional sensor data, which can be used to deviate from the initial motion plan and implement a replacement motion plan to transfer the package to the task location.

A de-palletizing system comprises a three-dimensional scanner; a robotic arm; and a control unit connected to the three-dimensional scanner and the robotic arm. The three-dimensional scanner takes a picture of a top layer of a pallet and transmits picture data to the control unit. The control unit is configured to receive the picture data from the three-dimensional scanner, process the picture data to create a depth map of the individual products and determine locations of individual products, and control the robotic arm to move a product grouping from a pick up location to a product drop off location.

A pallet building apparatus for automatically building a pallet load of pallet load article units onto a pallet support including a frame defining a pallet building base, at least one articulated robot to transport and place the pallet load article units, a controller to control articulated robot motion and effect therewith a pallet load build, at least one three-dimensional, time of flight, camera to generate three-dimensional imaging of the pallet support and pallet load build, wherein the controller registers, from the three-dimensional camera, real time three-dimensional imaging data embodying different corresponding three-dimensional images of the pallet support and pallet load build, to determine, in real time, from the corresponding real time three-dimensional imaging data, a pallet support variance or article unit variance and generate in real time an articulated robot motion signal, the articulated robot motion signal being generated real time so as to be performed real time by the at least one articulated robot between placement of at least one pallet load article unit and a serially consecutive pallet load article unit enabling substantially continuous building of the pallet load build.

Pre-plating systems and related methods are disclosed. A pre-plating system includes a press, an infeed robot configured to deliver a structural member to the press, and an outfeed robot configured to remove the structural member from the press. The press is configured to secure a plate to the structural member while the structural member is held in position by at least one of the infeed robot or the outfeed robot. A pre-plating system includes a press, a transfer pedestal, a plate picking robot, and a press loading robot. The plate picking robot is configured to pick a plate from a container and position the plate on the transfer pedestal. The press loading robot is configured to transfer the plate to the press. The press is configured to press the plate into a structural member positioned within the press.

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.

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.

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.

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.