An autonomous control system includes an acquirer configured to acquire state data of a robot, visual data of the robot, and tactile data of the robot and a processor configured to decide on an action of the robot capable of accomplishing a task given to the robot on the basis of the state data, the visual data, and the tactile data. The processor generates first compressed data having a smaller number of dimensions than data obtained by combining the visual data and the tactile data by fusing and dimensionally compressing the visual data and the tactile data. The processor generates second compressed data having a smaller number of dimensions than the tactile data by dimensionally compressing the tactile data. The processor decides on the action on the basis of combined state data obtained by combining the state data, the first compressed data, and the second compressed data into one.

A controller of the robot apparatus performs approaching control for making a second workpiece approach a first workpiece and position adjustment control for adjusting a position of the second workpiece with respect to a position of the first workpiece. The approaching control includes control for calculating a movement direction and a movement amount of a position of the robot based on an image captured by a first camera, and making the second workpiece approach the first workpiece. The position adjustment control includes control for calculating a movement direction and a movement amount of a position of the robot based on an image captured by the first camera and an image captured by the second camera, and precisely adjusting a position of the first workpiece with respect to the second workpiece.

A system and method palletize containers having electrical terminals for charging electronic devices packaged therein. First, a stacking pattern is determined on the basis of the sizes, shapes, and locations of electrical terminals on both the pallets and the containers to be stacked. These data may be read, for example, with a computer vision system that uses an articulating robotic arm, and may be encoded in a two-dimensional barcode on each pallet and/or container. Next, the robotic arm stacks the container so that its terminals make electrical contact with terminals on the pallet, or on a previously-stacked layer of containers. Then, the placement is tested to ensure that a good electrical connection exists vertically through the entire stack. Once the pallet is finalized, all electronic devices carried thereon may be simultaneously charged during transit or storage.

An example computer-implemented method includes receiving, from one or more vision components in an environment, vision data that captures features of the environment, including object features of an object that is located in the environment, and prior to a robot manipulating the object: (i) determining based on the vision data, at least one first adjustment to a programmed trajectory of movement of the robot operating in the environment to perform a task of transporting the object, and (ii) determining based on the object features of the object, at least one second adjustment to the programmed trajectory of movement of the robot operating in the environment to perform the task, and causing the robot to perform the task, in accordance with the at least one first adjustment and the at least one second adjustment to the programmed trajectory of movement of the robot.

A method for training a control arrangement for a controlled system. The control arrangement includes a regulation device and an actuator that operates according to a control strategy. The method includes the generation of control actions by the regulation device, each control action being generated by detecting measured variables that indicate a state of the controlled system, ascertaining a correction term for the detected measured variables by the actuator according to the control strategy, adapting the detected measured variables using the correction term for the detected measured variables, and generating the control action by supplying the adapted measured variables to the regulation device as the actual value. The method further includes training the control strategy by reinforcement learning for maximizing the gain that is achieved by the generated control actions.

The present disclosure provides is a method and device for accurately estimating a pose of a charging socket of an electric vehicle regardless of a shape of the charging socket, so that an electric vehicle charging robot may precisely move a charging connector toward the charging socket of the electric vehicle and couple the charging connector to the charging socket. According to an aspect of an exemplary embodiment, a method of estimating the pose of the charging socket of an electric vehicle includes: acquiring an RGB image and a depth map of the charging socket; detecting a keypoint of the charging socket based on the RGB image; deriving a first estimated pose of the charging socket based on the depth map; and deriving a second estimated pose of the charging socket based on the keypoint of the charging socket and the first estimated pose.

The present application discloses a robotic control system, and a method and a computer system for controlling a robot. The robotic control system includes a memory and one or more processors coupled to the memory. The memory is configured to store configured to store a model of a robot having a plurality of axes of control including at least a linear axis and one or more rotational axes. The one or more processors are configured to use the model to control the robot to perform a task, including by sending to the robot a set of control signals to cause the robot to move with respect to two or more of said axes of control including at least the linear axis.

A program generation apparatus according to one or more embodiments may extract, from a series of motions defined in a motion program, a motion to be corrected based on a difference in attribute between a first component indicated as a target of a component change and a second component to replace the first component, and generate a new motion program by correcting a command value of the extracted motion to compensate for the difference in the attribute.

A method for controlling a servomotor with a converter includes monitoring a circuit of a direct-voltage DC link that is connected to an input circuit for flow of an electric current; switching off a first switching device to end the supply of the direct-voltage DC link from an electrical grid if a stop signal occurs; braking the servomotor by control of power semiconductor switches of an inverter circuit in a regenerative braking operation, to reduce the rotation speed of the servomotor, if the monitoring detects that an electric current is not flowing after the first switching device has been switched off; and switching off a second switching device to prevent feeding electrical energy from the direct-voltage DC link into the servomotor if the monitoring detects a flow of electric current after the first switching device has been switched off.

A welding system includes a welding robot provided with a torch, and a welding robot control program creation device. The welding robot control program creation device is configured to acquire position information of a welding start point and a welding end point on a workpiece, and posture information capable of specifying a posture of the torch with respect to a weld line at a welding teaching point on the weld line connecting the welding start point and the welding end point, and create a welding robot control program for performing welding from the welding start point to the welding end point based on the position information and the posture information. The welding robot is configured to perform welding on the workpiece based on the welding robot control program.