One exemplary embodiment is a system comprising an operator input device structured to move in response to operator-applied force and to selectably output feedback force to the operator. A first computing system is structured to receive input from the operator input device and provide an output. A second computing system is structured to receive the output and provide a robot control command subject to a force constraint. An industrial robot system is in operative communication with the second computing system and comprises a robotic arm structured to move in response to the command. The second computing system is structured process the output to impose a force constraint using a dual threshold hysteresis control. The first computing system is structured to apply a feedback force to the operator input device correlated to force associated with the industrial robot system.

A contact control device (100) includes a disturbance correction timing control unit (42) that selectively outputs a first reference speed signal indicating a first reference speed or a second reference speed signal indicating a second reference speed lower than the first reference speed. When a movable part (12) comes closer to a second component (B) beyond a first reference position between a fixed part (11) and the second component (B), the disturbance correction timing control unit (42) switches its output signal from the first reference speed signal to the second reference speed signal and switches a gain in proportional compensation from a first gain to a second gain lower than the first gain.

The present invention relates to methods for learning a robot task and robots systems using the same. A robot system may include a robot configured to perform a task, and detect force information related to the task, a haptic controller configured to be manipulatable for teaching the robot, the haptic controller configured to output a haptic feedback based on the force information while teaching of the task to the robot is performed, a sensor configured to sense first information related to a task environment of the robot and second information related to a driving state of the robot, while the teaching is performed by the haptic controller for outputting the haptic feedback, and a computer configured to learn a motion of the robot related to the task, by using the first information and the second information, such that the robot autonomously performs the task.

A robot system according to the present disclosure includes a robot installed in a work area, a manipulator configured to be gripped by an operator and manipulate the robot, a sensor disposed at a manipulation area and configured to wirelessly detect positional information and posture information on the manipulator, and a control device which calculates a locus of the manipulator based on the positional information and the posture information on the manipulator detected by the sensor, and operates the robot on real time.

Embodiments of this application provide a method for preparing a thin film piezoresistive material, a thin film piezoresistive material, a robot, and a device. The method includes: determining a mass ratio of conductive particles to a cross-linked polymer in preparation of the thin film piezoresistive material, a value range of the mass ratio being 3:97 to 20:80; dispersing the conductive particles and the cross-linked polymer in a solvent according to the mass ratio, to obtain a first dispersion; and curing the first dispersion by using a liquid dropping method within a temperature range of 25° C. to 200° C., to obtain the thin film piezoresistive material. The technical solutions provided by the embodiments of this application provide a method for preparing a thin film piezoresistive material through liquid dropping, thereby effectively controlling the thickness of the piezoresistive material, so that the prepared thin film piezoresistive material has a relatively small thickness.

A coupling device (16, 116, 216, 316) configured optimally to communicate between a first and a second admittance controller and actuator assembly, the first and the second admittance control and actuator assembly respectively having a first and a second admittance controller (12a, 12b) configured to drive a respective first and a second actuator and each of the first and the second actuator being respectively connected to a first body having a first mass and a second body having a second mass, wherein the coupling device (16, 116, 216, 316) comprises: an input port having a first input for receiving a first input force signal (f1) from the first admittance controller and actuator assembly (12a) and a second input for receiving a second input force signal (f2) from the second admittance controller and actuator assembly (12b), and a processor adapted to derive a first output force signal for output to the first admittance controller and actuator assembly based on a Lagrange multiplier dependent on a comparison of the first input force signal and the second input force signal.

A robot system (1) includes the robot (10), a motion sensor (11), a surrounding environment sensor (12, 13), an operation apparatus (21), a learning control section (41), and a relay apparatus (30). The robot (10) performs work based on an operation command. The operation apparatus (21) detects and outputs an operator-operating force applied by the operator. The learning control section (41) outputs a calculation operating force. The relay apparatus (30) outputs the operation command based on the operator-operating force and the calculation operating force. The learning control section (41) estimates and outputs the calculation operating force by using a model constructed by performing the machine learning of the operator-operating force, the surrounding environment data, the operation data, and the operation command based on the operation data and the surrounding environment data outputted by the sensors (11 to 13), and the operation command outputted by the relay apparatus (30).

A coupling device (16, 116, 216, 316) configured optimally to communicate between a first and a second admittance controller and actuator assembly, the first and the second admittance control and actuator assembly respectively having a first and a second admittance controller (12a, 12b) configured to drive a respective first and a second actuator and each of the first and the second actuator being respectively connected to a first body having a first mass and a second body having a second mass, wherein the coupling device (16, 116, 216, 316) comprises: an input port having a first input for receiving a first input force signal (f1) from the first admittance controller and actuator assembly (12a) and a second input for receiving a second input force signal (f2) from the second admittance controller and actuator assembly (12b), and a processor adapted to derive a first output force signal for output to the first admittance controller and actuator assembly based on a Lagrange multiplier dependent on a comparison of the first input force signal and the second input force signal.

The application relates to a haptic system comprising a haptic device that has an end effector terminal and a transmission structure which can generate a translational movement as an output variable, said translational movement extending from the transmission structure to the end effector terminal via a boom such that the end effector terminal moves in a manner that is perceptible to a user, the transmission structure being formed by means of driven linear shafts. The application further relates to a method for operating a haptic system comprising a haptic device.

A robot system according to the present disclosure includes a robot installed in a work area, a manipulator configured to be gripped by an operator and manipulate the robot, a sensor disposed at a manipulation area and configured to wirelessly detect positional information and posture information on the manipulator, and a control device which calculates a locus of the manipulator based on the positional information and the posture information on the manipulator detected by the sensor, and operates the robot on real time.