A pick & place operation picking a non-electric component and placing the picked component onto a component-carrier and a connect operation connecting the placed component with the component-carrier by implementing a connection technology on a hybrid, at least reactive and deliberative machine architecture based on a “machine world model” as a digital twin to formulate correct machine-behavioral sets being used during machine run-time as well as an “machine workflow”, and executing by machine motion generation including a collision-free motion or path planning of a machine within a machine workspace primary kinematic machine-movement-sequences enabling the pick & place operation and secondary kinematic machine-movement-sequences enabling the connect operation, and enabling the execution via the machine motion generation by initializing the “machine world model” according to a configuration file configuring the machine and the machine workspace and instantiating the “machine workflow” and updating the “machine world model” with a design of the component-carrier.

In one embodiment, a system for inspecting an object comprises a first camera for inspecting a first surface of the object, and a second camera for inspecting a second surface of the object. The object may be placed upon a support structure during simultaneous inspection by the first camera and the second camera. At least one roller is arranged to selectively engage the object when the object is placed upon the support structure, wherein the at least one roller is adapted for circumferential rotation relative to the support structure. Rotation of the at least one roller causes a corresponding circumferential rotation of the object relative to the first and second cameras.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing planning for robotic placement tasks. One of the methods includes determining an initial in-hand state for a grasped object. A show pose for the grasped object is determined, and the object is moved to the show pose. A refined in-hand state for the grasped object is determined based on the show pose, and a placement plan is determined based on the refined in-hand state for the grasped object.

A work machine includes a pickup member configured to pick up a component; a storage device configured to store positional information on multiple pickup positions where the pickup member can pick up the component; a recognition device configured to optically recognize a multiple of the component including the pickup target; and a control device configured to select, from the multiple pickup positions of the pickup target component, one pickup position which is less likely to interfere with other components based on the positional information and a recognition result from the recognition device, and cause the pick member to pick up the pickup target component at the one selected pickup position.

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.

Methods, systems, and software for controlling object picking and placement by a robot system are disclosed. The method includes assigning machine learning training data of a machine learning model for an object. The machine learning training data includes a plurality of known grasp location labels assigned to the object positioned in a plurality of different object poses. The method includes providing the object in a work space of the robot system. For the object in the work space in a first pose of the plurality of different object poses, the method includes: mapping a first candidate grasp location on the object; executing robotic movements for the first candidate grasp location on the object; and evaluating a result of the executing for the first candidate grasp location according to at least one predetermined performance criteria.

An arrangement for handling objects on an object transporting device includes an industrial robot and an object handling control device. The device estimates candidate handling positions (OP1, OP2, OP3, OP4, OP5, OP6, OP7) for at least one candidate object based on a first assumption; determines for each candidate handling position whether it lies within a working volume (wv1) of the robot; selects one of the candidate positions (OP1) at a first decision instant, the selection being at least partially based on the result of the determining; and handles an object at an actual handling position corresponding to the selected candidate handling position, the handling being performed after a usage time of the robot, the usage time including the time for moving the robot from the robot position at the first decision instant to the actual handling position, and the time for handling the object.

A control device comprises a first interface, a second interface, a processor, and a third interface. A first interface is configured to acquire a captured image of an article. A second interface is configured to transmit and receive data to and from an input/output device. A processor is configured to cause the input/output device to display an article image based on the captured image, receive an input of a position and an angle of a grip portion model of a grip portion that grips the article from the input/output device through the second interface, display the grip portion model on the article image, and generate a gripping plan. A third interface configured to transmit the gripping plan to a control unit of a gripping device including the grip portion.

An trajectory information generating unit for generating trajectory information defining a trajectory for which a picking hand picks a work at a first position and arranges the work at a second position, an execution control unit for operating a picking apparatus based on trajectory information generated by the trajectory information generating unit, and an execution time estimating unit for estimating a period of time from when the picking apparatus receives an instruction for starting an operation on a work to a time when the operation of the picking apparatus on the work is ended are included. The trajectory information generating unit may adjust an amount of calculation based on an estimation result of the execution time estimating unit.

The present invention easily generates training data needed for generating a training model for identifying a position for retrieving a bulk-loaded work piece. An information processing device, according to the present invention, for processing information for retrieving a work piece using a hand, said device comprising: a reception unit that receives retrieval conditions including information about the hand or the work piece; a pre-processing unit that at least derives the position of the center of gravity of the work piece on the basis of a 3D CAD model of the work piece; and a first processing unit that, on the basis of the derived position of the center of gravity of the work piece, derives sectional features of the 3D CAD model of the work piece according to the retrieval conditions.