A robot includes a base, a robot arm having a first arm coupled to the base and rotating about a first axis, and a force detection unit provided in the base and detecting a force acting on the base or the robot arm, wherein the first arm is coupled to the base in a position shifted from a first center line passing through a center of the base and being parallel to the first axis, and a second center line passing through a center of the force detection unit and being parallel to the first axis is closer to the first axis than the first center line.

The invention relates to a device (10) interchangeably usable by a robot (12) and a human (14). The present invention also relates to a system (100) comprising such a device, a method of operating such a device (10), and a computer readable medium (46). The invention can for example be applied in servicing of heavy-duty vehicles.

Embodiments provide a system suitable for handling and correcting elastic materials and a method thereof. In the embodiments, a system for handling and correcting elastic materials includes a workbench, and also includes: an image recognition device, a control unit, a motion robot and a correction device. The present disclosure is intended to provide a system for handling and correcting elastic materials and a method thereof, relying on automatic equipment to perform correction operations, with high degree of automation and precise control.

Systems and methods for an inspection robot having replaceable sensor sled portions are disclosed. An example system may include: an inspection robot including a plurality of payloads; a plurality of arms, each of the plurality of arms pivotally mounted to one of the plurality of payloads; and a plurality of sleds, each sled mounted to one of the plurality of arms. At least one of the plurality of sleds includes an upper portion coupled to a replaceable lower portion, where the replaceable lower portion includes a portion of a delay line for a sensor of the inspection robot.

Noise reduction in a robot system includes the use of a gesture library that pairs noise profiles with gestures that can be performed by the robot. A gesture to be performed by the robot is obtained, and the robot performs the gesture. The robot's performance of the gesture creates noise, and when a user speaks to the robot while the robot performs a gesture, incoming audio includes both user audio and robot noise. A noise profile associated with the gesture is retrieved from the gesture library and is applied to remove the robot noise from the incoming audio.

A robotic system comprising: a multi-axis robot; one or more sensors located on the multi-axis robot; a damping system configured to apply a resistive force to the multi-axis robot, thereby to resist movement of the multi-axis robot; and a controller coupled to the one or more sensors and the damping system, the controller being configured to: receive sensor measurements from the one or more sensors; and control, based on the received sensor measurements, the damping system thereby to control the resistive force applied by the damping system to the multi-axis robot.

An articulated arm system is disclosed that includes an articulated arm including an end effector, and a robotic arm control systems including at least one sensor for sensing at least one of the position, movement or acceleration of the articulated arm, and a main controller for providing computational control of the articulated arm, and an on-board controller for providing, responsive to the at least one sensor, a motion signal that directly controls at least a portion of the articulated arm.

A system is described for configuring another system, e.g., a robotics system. The other system interacts with an environment according to a deterministic policy by repeatedly obtaining, from a sensor, sensor data indicative of a state of the environment, determining a current action, and providing, to an actuator, actuator data causing the actuator to effect the current action in the environment. To configure the other system, the system optimizes a loss function based on an accumulated reward distribution with respect to a set of parameters of the policy. The accumulated reward distribution includes an action probability of an action of a previous interaction log being performed according to the current set of parameters. The action probability is approximated using a probability distribution defined by an action selected by the deterministic policy according to the current set of parameters.

A control device controlling a robot including a robot arm, a drive section causing the robot arm to pivot around a pivot axis, a shaft that is provided at a position of the robot arm different from the pivot axis and that moves parallel to the pivot axis, and an angular velocity sensor that is provided in the robot arm and that detects angular velocity around an axis orthogonal to an axial direction of the pivot axis and parallel to a plane including the pivot axis and an axis of the shaft, the control device includes a processor that is configured to control the robot, wherein the processor is configured to perform feedback control on the drive section based on the angular velocity.

A method and system for task execution in dynamic heterogeneous robotic environment is disclosed. The method includes extracting data associated with a plurality of data categories and further deriving a plurality of factors from the extracted data. The method further includes determining a plurality of correlations among the plurality of factors based on the deep learning network. The method further includes deriving a plurality of sentiment parameters for a set of factors from the plurality of factors based on the plurality of correlations. The method may further includes simulating execution of the at least one current task by employing a plurality of robots. The method may further includes iteratively re-adjusting at least one of the plurality of sentiment parameters based on reinforcement learning performed on a result of the simulating. The method may further includes executing the at least one current task by employing the plurality of robots.