A force sensor diagnostic device that diagnoses a force sensor provided in a robot, the force sensor disposed near an installation surface on which the robot is installed and detecting a force and a moment applied to the robot from an outside. The device includes a calculation unit that calculates a theoretical value of the force and a theoretical value of the moment detected by the force sensor, a determination unit that determines whether the force sensor is distorted by comparing an actually measured value of the force and an actually measured value of the moment detected by the force sensor with the theoretical values of the force and the moment, and a notification unit that notifies a determination result from the determination unit.

A method of calibrating a virtual force sensor of a robot manipulator, wherein in a plurality of poses, the method comprises: applying an external wrench to the robot manipulator ascertaining an estimate of the external wrench, ascertaining a respective cost function based on a difference between the determined estimate of the external wrench and a specified external wrench, ascertaining a respective calibration function by minimizing the respective cost function, and storing the respective calibration function in a data set of all calibration functions with assignment of the respective calibration function to a respective pose for which the respective calibration function was ascertained.

System for automatically manipulating primary packaging in secondary packaging, comprising a robot having at least one robot arm with a clamping gripper installed at a tool centre point, wherein each tool centre point has a force-torque sensor, an image recording module for recording images of at least the upper segment of the primary packaging, comprising at least two stereo cameras for recording 3-D images, and one or more processors for providing a three-dimensional point cloud, controlling the image recording module and controlling the robot on the basis of the analysis of the three-dimensional point cloud and the measurements from the force-torque sensors.

The present disclosure discloses an autonomous mobile grabbing method for a mechanical arm based on visual-haptic fusion under a complex illumination condition, which mainly includes approaching control over a target position and feedback control over environment information.

According to the method, under the complex illumination condition, weighted fusion is conducted on visible light and depth images of a preselected region, identification and positioning of a target object are completed based on a deep neural network, and a mobile mechanical arm is driven to continuously approach the target object; in addition, the pose of the mechanical arm is adjusted according to contact force information of a sensor module, the external environment and the target object; and meanwhile, visual information and haptic information of the target object are fused, and the optimal grabbing pose and the appropriate grabbing force of the target object are selected.

By adopting the method, the object positioning precision and the grabbing accuracy are improved, the collision damage and instability of the mechanical arm are effectively prevented, and the harmful deformation of the grabbed object is reduced.

In an embodiment, a method includes determining a given material to manipulate to achieve a goal state. The goal state can be one or more deformable or granular materials in a particular arrangement. The method further includes, for the given material, determining, a respective outcome for each of a plurality of candidate actions to manipulate the given material. The determining can be performed with a physics-based model, in one embodiment. The method further can include determining a given action of the candidate actions, where the outcome of the given action reaching the goal state is within at least one tolerance. The method further includes, based on a selected action of the given actions, generating a first motion plan for the selected action.

A machining system having plural machining devices installed at plural points in a robot arm. the machining system carrying out machining to a processed object made of metal be by using these machining devices, the machining system further having a control device that controls drive of the machining devices so as to offset processing reaction forces by at least one of a thrust force and a torque to be obtained when the machining devices carry out machining to the processed object simultaneously between the machining devices.

A mechanical translation apparatus includes a translation stage and a translation assembly operatively connected to the translation stage so as to impart linear motions to the translation stage substantially free of rotational motions. The translation assembly includes a plurality of at least three arms pivotably connected to the translation stage at a first end of each arm of the plurality of at least three arms. The mechanical translation apparatus also includes a base assembly in which each arm of the plurality of at least three arms is also rotationally connected to the base assembly at a second end of each arm. Each arm of the plurality of at least three arms includes three rigid elongate structures arranged substantially parallel and non-coplanar with respect to each other so as to act in cooperation to cancel torques so that substantially purely linear motion is imparted to the translation stage by the plurality of at least three arms, and the translation assembly constrains motion of the translation stage to be substantially purely translational motion free of rotational motion. A robot includes the mechanical translation apparatus.

A method of generating a control program, wherein the method includes: executing an application by the first robot manipulator, at the same time, determining trajectory data and/or wrench data, determining robot commands from a stored time series, the robot commands being principal elements of the control program for the robot manipulator without relation to design conditions of a first robot manipulator, and generating the control program for a second robot manipulator based on the stored robot commands and based on the design conditions of the second robot manipulator.

Disclosed is a transporting robot which executes a mounted artificial intelligence (AI) algorithm and/or machine learning algorithm and communicates with different electronic devices and external servers in a 5G communication environment. The transporting robot includes a wheel driver, a loading box, and a robot controller. The transporting robot is provided such that a transporting service using an autonomous robot may be provided.

An end effector adaptor device for a robotic arm may have a body adapted to be secured to a working end of a robotic arm at a proximal face, the body having a distal face configured for connection of an end effector thereto. A proximal connector is in the proximal face, the proximal connector configured to be connected to a complementary connector at the working end of the robotic arm for signal and power transmission between the robotic arm and the body. A distal connector is in the distal face, the distal connector configured to be connected to a complementary connector at the end effector connected to the distal face for signal transmission and/or power transmission between the body and the end effector. Circuitry is between the proximal connector and the distal connector.