New Method for Global Identification of the Joint Drive Gains of Robots using a Known Payload Mass

Chapitre d'équation 1 Section 1

Maxime Gautier (1) , Sébastien Briot (1)

1 IRCCyN - Institut de Recherche en Communications et en Cybernétique de Nantes

Off-line robot dynamic identification methods are mostly based on the use of the Inverse Dynamic Identification Model (IDIM), which calculates the joint force/torque that is linear in relation to the dynamic parameters, and on the use of linear least squares technique to calculate the parameters (IDIM-LS technique). The joint forces/torques are calculated as the product of the known control signal (the current reference) by the joint drive gains. Then it is essential to get accurate values of joint drive gains to get accurate identification of inertial parameters. In this paper it is proposed a new method for the identification of the total joint drive gains in one step using available joint sampled data given by the standard controller of the moving robot and using only the weighted mass of a payload, without any CAD values of its inertial parameters. A new inverse dynamic model calculates the current reference signal of each joint j that is linear in relation to the dynamic parameters of the robot, to the inertial parameters of a known mass fixed to the end-effector, and to the inverse of the joint j drive gain. This model is calculated with current reference and position sampled data while the robot is tracking one reference trajectory without load on the robot and one trajectory with the known mass fixed on the robot. Each joint j drive gain is calculated independently by the weighted LS solution of an over-determined linear systems obtained with the equations of the joint j. The method is experimentally validated on an industrial Stäubli RX-90 robot.

Domaines: Génie mécanique [physics.class-ph]; Génie mécanique [physics.class-ph]

Maxime Gautier, Sébastien Briot. New Method for Global Identification of the Joint Drive Gains of Robots using a Known Payload Mass. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2011), Sep 2011, San Francisco, France. ⟨hal-00609073⟩