A computing system and method for estimating friction and/or center of mass (CoM) are presented. The system may perform the method by selecting at least one of: (i) a first joint from among a plurality of joints, or (ii) a first arm segment from among a plurality of arm segments. The computing system further outputs a set of one or more movement commands for causing robot arm movement that includes relative movement between the first arm segment and a second arm segment via the first joint, and receiving a set of actuation data and a set of movement data associated with the first joint or the first arm segment. The computing system further determines, based on the set of actuation data and the set of movement data, at least one of: (i) a friction parameter estimate or (ii) a CoM estimate.

In a method for compensating for friction of a multi-degree-of-freedom cooperative robot including a plurality of joints, the method for compensating for friction of the multi-degree-of-freedom cooperative robot, according to an embodiment of the present invention, comprises the steps of: generating a motion of a cooperative robot for friction compensation; driving the plurality of joints on the basis of the generated motion of the cooperative robot; receiving friction identification data from the cooperative robot; and calculating a friction model function from the received friction identification data.

A method of controlling a robot arm with robot joints, where the joint motors of the joints are controlled based on a signal generated based on the friction torque (formula I) of at least one of the input/outside of the robot joint transmission and the robot joint transmission torque (formula II) between the input side and the output side of the transmission. The friction torque is determined based on: at least two of the angular position of the motor axle; the angular position of the output axle and/or the motor torque provided to the motor axle by the joint motor. The robot joint transmission torque is determined based on: at least one of the angular position of the output axle; the angular position of the output axle and/or the angular position of the motor axle; the angular position of the motor axle and the motor torque provided to the motor axle by the joint motor.

A computing system and method are presented. The computing system may store sensor data which includes: (i) a set of movement data, and (ii) a set of actuation data. The computing system may divide the sensor data into training data and test data by: (i) selecting, as the training data, movement training data and corresponding actuation training data, and (ii) selecting, as the test data, movement test data and corresponding actuation test data. The computing system may determine, based on the movement training data and the actuation training data, at least one of: (i) a friction parameter estimate or (ii) a center of mass (CoM) estimate, and may determine actuation prediction data based on the movement test data and based on the at least one of the friction parameter estimate or the CoM estimate. The computing system may further determine residual data, and determine a value for an error parameter.

A computing system and method are presented. The computing system may store sensor data which includes: (i) a set of movement data, and (ii) a set of actuation data. The computing system may divide the sensor data into training data and test data by: (i) selecting, as the training data, movement training data and corresponding actuation training data, and (ii) selecting, as the test data, movement test data and corresponding actuation test data. The computing system may determine, based on the movement training data and the actuation training data, at least one of: (i) a friction parameter estimate or (ii) a center of mass (CoM) estimate, and may determine actuation prediction data based on the movement test data and based on the at least one of the friction parameter estimate or the CoM estimate. The computing system may further determine residual data, and determine a value for an error parameter.

A dragging demonstration system and method. The dragging demonstration system comprises: a model identification module configured to build a static model of a robot and identify model parameters, wherein the static model comprises a gravity model and a Coulomb friction model; a feedforward compensation module configured to convey the identified model parameters to a current ring of each joint motor of the robot in a feedforward way according to the identified model parameters; and a data recording module configured to record the position information of each joint of the robot so that the robot can repeat the demonstration action. The system and method can make a user push the robot quite easily to implement dragging demonstration.

A computing system and method for estimating friction and/or center of mass (CoM) are presented. The system may perform the method by selecting at least one of: (i) a first joint from among a plurality of joints, or (ii) a first arm segment from among a plurality of arm segments. The computing system further outputs a set of one or more movement commands for causing robot arm movement that includes relative movement between the first arm segment and a second arm segment via the first joint, and receiving a set of actuation data and a set of movement data associated with the first joint or the first arm segment. The computing system further determines, based on the set of actuation data and the set of movement data, at least one of: (i) a friction parameter estimate or (ii) a CoM estimate.

A computing system and method for estimating friction and/or center of mass (CoM) are presented. The system may perform the method by selecting at least one of: (i) a first joint from among a plurality of joints, or (ii) a first arm segment from among a plurality of arm segments. The computing system further outputs a set of one or more movement commands for causing robot arm movement that includes relative movement between the first arm segment and a second arm segment via the first joint, and receiving a set of actuation data and a set of movement data associated with the first joint or the first arm segment. The computing system further determines, based on the set of actuation data and the set of movement data, at least one of: (i) a friction parameter estimate or (ii) a CoM estimate.

The various embodiments herein relate to robotic surgical systems and devices that use force and/or torque sensors to measure forces applied at various components of the system or device. Certain implementations include robotic surgical devices having one or more force/torque sensors that detect or measure one or more forces applied at or on one or more arms. Other embodiments relate to systems having a robotic surgical device that has one or more sensors and an external controller that has one or more motors such that the sensors transmit information that is used at the controller to actuate the motors to provide haptic feedback to a user.

A computing system and method are presented. The computing system may store sensor data which includes: (i) a set of movement data, and (ii) a set of actuation data. The computing system may divide the sensor data into training data and test data by: (i) selecting, as the training data, movement training data and corresponding actuation training data, and (ii) selecting, as the test data, movement test data and corresponding actuation test data. The computing system may determine, based on the movement training data and the actuation training data, at least one of: (i) a friction parameter estimate or (ii) a center of mass (CoM) estimate, and may determine actuation prediction data based on the movement test data and based on the at least one of the friction parameter estimate or the CoM estimate. The computing system may further determine residual data, and determine a value for an error parameter.