After a forward end of a workpiece is inserted into a through-hole and fitting is started, a follow operation of moving the workpiece to follow the shape of the through-hole is performed during the movement of the workpiece in a fitting direction. At this time, the workpiece is fitted into the through-hole while a control point of a robot is changed in a direction opposite to the fitting direction according to the amount of movement of the workpiece in the fitting direction.

An electronic apparatus includes a camera; a gripper configured to grip a grip target object; a memory configured to store a neural network model; and a processor configured to: obtain movement information and rotation information of the gripper by inputting at least one image captured by the camera to the neural network model, and control the gripper based on the movement information and the rotation information. The at least one image includes at least a part of the gripper and at least a part of the grip target object, and the neural network model is configured to output the movement information and the rotation information for positioning the gripper to be adjacent to the grip target object, based on the at least one image, the movement information includes one of a first direction movement, a second direction movement, or a movement stop of the gripper, and the rotation information includes one of a first direction rotation, a second direction rotation, or a non-rotation of the gripper.

A simulation method of specifying a relative position between a first base of a first robot manipulator and a second base of a second robot manipulator, including: determining a first working area of the first robot manipulator, wherein the first working area determines a finite plurality of tuples from possible positions of the first end effector and possible orientations of the first end effector in respective positions of the first end effector; determining, for each of a specified plurality of possible relative positions between the first base and the second base, a number of the tuples from the first working area as evaluation variables, for which a second end effector is capable of being positioned in a predefined orientation and/or at a predefined distance relative to the first end effector; and determining and outputting the relative position between the first base and the second base with a highest evaluation variable.

A computer system learns how to grasp objects using a robot arm. The system generates masks of objects shown in an image. A grasp generator generates proposed grasps for the objects based on the masks. A grasp network evaluates the proposed grasps and generates scores representing the likelihood that the proposed grasps will be successful. The system makes an innovative use of masks to generate high-quality grasps using fewer computations than existing systems.

An example method includes receiving task identification information indicative of a manufacturing task to be performed on a workpiece, wherein the workpiece transfer system comprises a rail and a plurality of arms coupled to the rail, wherein each arm comprises (i) a plurality of arm linkages coupled at respective joints, (ii) an arm controller in communication with the supervisory controller, and (iii) respective joint controllers in communication with the arm controller and configured to actuate respective rotary actuators at the respective joints to move the plurality of arm linkages relative to each other: retrieving a motion plan corresponding to the manufacturing task and the workpiece: sending command signals to respective arm controllers to communicate respective command signals to the respective joint controllers and execute the motion plan; and once the final desired configuration is achieved, commanding the respective arm controllers to lock the respective joints.

An industrial robot adapted for operation in a factory environment includes: sensors, actuators, a robot controller and a wireless interface configured to establish a sidelink to a further industrial robot or a group of industrial robots after a successful proximity verification. The industrial robot is configured to participate in execution of a utility task, which is carried out in collaboration with the further industrial robot or at least some members of the group of industrial robots, said collaboration including an exchange of operational data over the sidelink. An example utility task is the coordinated transfer of an object by multiple participating industrial robots. Another example is the collecting of map information by multiple participating industrial robots.