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.

One embodiment can provide a robotic system. The system can include a machine-vision module, a robotic arm comprising an end-effector, a robotic controller configured to control movements of the robotic arm, and an error-compensation module configured to compensate for pose errors of the robotic arm by determining a controller-desired pose corresponding to a camera-instructed pose of the end-effector such that, when the robotic controller controls the movements of the robotic arm based on the controller-desired pose, the end-effector achieves, as observed by the machine-vision module, the camera-instructed pose. The error-compensation module can include a machine learning model configured to output an error matrix that correlates the camera-instructed pose to the controller-desired pose.

Provided is an apparatus for piston insertion, including an insertion robot having a plurality of robot arms connected by a plurality of articulated joints, a piston insertion module directly mounted on the insertion robot, gripping a piston assembly, and inserting the piston assembly into a cylinder bore of a cylinder block, and a controller controlling an operation of the insertion robot and an operation of the piston insertion module.

A computer-implemented method comprising, receiving data representing a successful trajectory for an insertion task using a robot to insert a connector into a receptacle, performing a parameter optimization process for the robot to perform the insertion task. This parameter optimization includes defining an objective function that measures a similarity of a current trajectory generated with a current set of parameters to the successful trajectory and repeatedly modifying the current set of parameters and evaluating the modified set of parameters according to the objective function until generating a final set of parameters.

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.

Provided is an automotive glass setting apparatus, including a setting base supporting a glass having a plurality of edges, a plurality of alignment units allowing the glass to be aligned with the setting base; a scanning unit scanning the edges of the glass, a plurality of moving mechanisms moving the plurality of alignment units, and a controller controlling the moving mechanisms based on data scanned by the scanning unit to align a center of the glass with a center of the setting base.

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.

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.

An approach to positioning one or more robotic arms in an assembly system may be described herein. For example, an apparatus may include a first robotic arm having a distal end and a proximal end. The distal end may be configured for movement and the proximal end may secure the first robotic arm. The apparatus may further include a camera connected with the distal end of the first robotic arm. The camera may be configured to capture image data of a marker connected with a second robotic arm and provide the image data to a computer. The computer may generate a set of instructions for the first robotic arm based on the image data of the marker. The movement of the first robotic arm may be caused by the computer according to the generated set of instructions.

A control device for a dishwashing system includes processing circuitry configured to control operation of a work device that performs an operation related to a washing rack that is placeable on each of a plurality of support surfaces extending in substantially the same plane, the plurality of support surfaces including a first support surface, a second support surface disposed in association with a dishwasher capable of washing a dish in the washing rack, and a third support surface; and control the work device to operate such that the washing rack is transferred from the first support surface and returned to the first support surface via the second support surface and via the third support surface. A direction in which the washing rack is carried into the dishwasher and a direction in which the washing rack is carried out of the dishwasher form a substantially right angle as viewed from above.