Patent classifications
G05B2219/37373
Estimating joint friction and tracking error of a robotics end effector
A computerized method for estimating joint friction in a joint of a robotic wrist of an end effector. Sensor measurements of force or torque in a transmission that mechanically couples a robotic wrist to an actuator, are produced. Joint friction in a joint of the robotic wrist that is driven by the actuator is computed by applying the sensor measurements of force or torque to a closed form mathematical expression that relates transmission force or torque variables to a joint friction variable. A tracking error of the end effector is also computed, using a closed form mathematical expression that relates the joint friction variable to the tracking error. Other aspects are also described and claimed.
Method and computing system for estimating parameter for robot operation
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.
METHOD FOR COMPENSATING FOR FRICTION OF MULTI-DEGREE-OF-FREEDOM COOPERATIVE ROBOT
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.
Estimating joint friction and tracking error of a robotics end effector
A computerized method for estimating joint friction in a joint of a robotic wrist of an end effector. Sensor measurements of force or torque in a transmission that mechanically couples a robotic wrist to an actuator, are produced. Joint friction in a joint of the robotic wrist that is driven by the actuator is computed by applying the sensor measurements of force or torque to a closed form mathematical expression that relates transmission force or torque variables to a joint friction variable. A tracking error of the end effector is also computed, using a closed form mathematical expression that relates the joint friction variable to the tracking error. Other aspects are also described and claimed.
DEVICE AND METHOD FOR DETECTING ABNORMALITY OF JOINT OF PARALLEL LINK ROBOT
A device and method for easily detecting an abnormality of a joint part of a delta-type parallel link robot having a link ball structure, by estimating a friction torque of a ball joint of the robot. A controller of the robot has: a control section configured to control the motion of the robot; a torque measurement section configured to measure or calculate, during the robot is operated, an amount of change in a drive torque, based on a current value of the motor, before and after the robot represents a specified posture where a sign of a relative angular velocity between a ball and a housing of the ball joint is changed; and a judgment section configured to judge that, when the measured amount of change in the drive torque exceeds a predetermined threshold, a friction state of the ball joint corresponding to the motor is abnormal.
METHOD FOR DETECTING AND EVALUATING A FRICTION STATUS AT A JOINT, ROBOTIC ARM AND COMPUTER PROGRAM PRODUCT
A method, a robot, and a computer program product for detecting and evaluating a friction status in at least one joint of a robotic arm, wherein, within the scope of a brake test program, at least one motor of a plurality of electric motors is driven automatically in a first rotational direction, wherein a detection of a first motor torque in the driven motor takes place during its rotation in the first rotational direction. The at least one motor is then driven in a second rotational direction opposite the first rotational direction, wherein a detection of a second motor torque in the driven motor takes place during its rotation in the second rotational direction. An automatic evaluation of the first motor torque and the second motor torque takes place in order to obtain the friction torque of the joint associated with the driven motor.
Method and computing system for determining a value of an error parameter indicative of quality of robot calibration
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.
METHOD AND COMPUTING SYSTEM FOR DETERMINING A VALUE OF AN ERROR PARAMETER INDICATIVE OF QUALITY OF ROBOT CALIBRATION
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.
ESTIMATING JOINT FRICTION AND TRACKING ERROR OF A ROBOTICS END EFFECTOR
A computerized method for estimating joint friction in a joint of a robotic wrist of an end effector. Sensor measurements of force or torque in a transmission that mechanically couples a robotic wrist to an actuator, are produced. Joint friction in a joint of the robotic wrist that is driven by the actuator is computed by applying the sensor measurements of force or torque to a closed form mathematical expression that relates transmission force or torque variables to a joint friction variable. A tracking error of the end effector is also computed, using a closed form mathematical expression that relates the joint friction variable to the tracking error. Other aspects are also described and claimed.
Parameter updating method, parameter updating system, and storage medium storing program
A method includes: acquiring time-series data of a control input and a control output; calculating a variable parameter that minimizes an evaluation function, based on observation values of the control input and the control output; and updating the variable parameter with the calculated variable parameter. The evaluation function includes: a first function part that evaluates an entire error that is a control error of the entire observation period and increases the output value as the entire error increases; and at least one of: a second function part that evaluates a sectional error that is a control error of a particular section in the observation period and increases the output value as the sectional error increases; and a third function part that evaluates an instantaneous error that is a control error of a particular time point in the observation period and increases the output value as the instantaneous error increases.