The present disclosure provides a humanoid robot and its control method and computer readable storage medium. The method includes: obtaining a current torque of a sole of the humanoid robot, an inclination angle of the sole, an inclination angle of a first joint of the humanoid robot, and an inclination angle of a second joint of the humanoid robot; calculating current feedforward angular velocities of motors of the first and second joints through the obtained information; calculating feedback angular velocities of the motors of the first and second joints; and obtaining inclination angles of the joints based on the feedforward angular velocities of the motors and the feedback angular velocities of the motors, and performing, through the motor of the second joint, a deviation control on the joints according to the inclination angles of the joints.

A method and system for robotic motion planning which perform dynamic velocity attenuation to avoid robot collision with static or dynamic objects. The technique maintains the planned robot tool path even when speed reduction is necessary, by providing feedback of a computed slowdown ratio to a tracking controller so that the path computation is always synchronized with current robot speed. The technique uses both robot-obstacle distance and relative velocity to determine when to apply velocity attenuation, and computes a joint speed limit vector based on a robot-obstacle distance, a maximum obstacle speed, and a computed stopping time as a function of the joint speed. Two different control structure implementations are disclosed, both of which provide feedback of the slowdown ratio to the motion planner as needed for faithful path following. A method of establishing velocity attenuation priority in multi-robot systems is also provided.

In a robotic surgical system, a control device is configured or programmed to scale rotation speeds of a plurality of joints axes of a robot arm at predetermined ratios such that the rotation speeds of the plurality of joint axes become equal to or lower than limit value with respect to a received operation amount.

A servo control device for controlling an end effector of a machine to follow a set reference trajectory by driving the machine using an actuator includes a feedforward compensation unit that performs feedforward compensation by outputting a feedforward signal for controlling the actuator on the basis of a position command signal inputted thereto, wherein input-output characteristics represented in a continuous-time system of the feedforward compensation unit are expressed by a transfer function having unstable zeros, and a step response of the feedforward compensation unit has an initial undershoot.

A robot controller includes a contact detection unit that detects contact of a welding wire protruding from a welding torch with a welding target, an override-value adjustment unit that sets and changes an override value for increasing or decreasing an operating speed of the robot from a predetermined speed, and a control unit which receives an operation signal from a teaching operation device and that controls the robot according to the operation signal at the operating speed based on the override value which is set by the override-value adjustment unit. When the contact of the welding wire with the welding target is detected by the contact detection unit, the control unit temporarily stops the robot, and the override-value adjustment unit decreases the override value.

A substrate transport device includes an arm, an end effector coupled to the arm, a driver configured to lift the arm so that the end effector receives a substrate, and a controller configured to control an output of the driver to change a lifting speed of the arm. While lifting the arm at a first speed to lift the end effector toward the substrate, the controller changes the lifting speed to a second speed that is lower than the first speed when the end effector starts to raise a height position of the substrate.

A teaching method for detecting external force applied to a robot arm, driving the robot arm with force control based on the external force, and teaching a position and a posture of the robot arm, the teaching method including gradually relaxing, according to an elapsed time from when operation of the robot arm is started or a movement amount of the robot arm from when the operation of the robot arm is started, a restrictive condition for restricting the driving of the robot arm.

A method and system for dynamic collision avoidance motion planning for industrial robots. An obstacle avoidance motion optimization routine receives a planned path and obstacle detection data as inputs, and computes a commanded robot path which avoids any detected obstacles. Robot joint motions to follow the tool center point path are used by a robot controller to command robot motion. The planning and optimization calculations are performed in a feedback loop which is decoupled from the controller feedback loop which computes robot commands based on actual robot position. The two feedback loops perform planning, command and control calculations in real time, including responding to dynamic obstacles which may be present in the robot workspace. The optimization calculations include a safety function which efficiently incorporates both relative position and relative velocity of the obstacles with respect to the robot.

A system for the intelligent obstacle avoidance of multi-axis robot arm includes a multi-axis robot arm and a host device. The multi-axis robot arm includes a plurality of knuckles and a plurality of connecting arms. The plurality of the connecting arms are alternately connected with the plurality of the knuckles. The host device is electrically connected with the multi-axis robot arm. The host device includes a database device, an operation control module and a signal transmission module. The database device, the operation control module and the signal transmission module are electrically connected. The signal transmission module transmits a control signal to the multi-axis robot arm for performing an optimum obstacle avoidance posture.

An example implementation for determining mechanically-timed footsteps may involve a robot having a first foot in contact with a ground surface and a second foot not in contact with the ground surface. The robot may determine a position of its center of mass and center of mass velocity, and based on these, determine a capture point for the robot. The robot may also determine a threshold position for the capture point, where the threshold position is based on a target trajectory for the capture point after the second foot contacts the ground surface. The robot may determine that the capture point has reached this threshold position and based on this determination, and cause the second foot to contact the ground surface.