External Joint Torques Estimation for a Position-Controlled Manipulator Employing an Extended Kalman Filter

Abstract

Industrial robots are required to interact with the surrounding environment to perform a given task (e.g., an assembly task). However, standard industrial robots are commonly position-controlled. Therefore, there is the need to implement an outer compliance controller to guarantee a safe interaction. Such compliance controllers require force/torque measurements to close the loop, and most of the industrial manipulators available on the market do not have embedded force/torque sensor(s), requiring additional efforts (i.e., additional costs and implementation resources) for such integration in the robotic setup. To provide a standard industrial sensorless position-controlled robot with the capabilities to execute an interaction task, the proposed paper defines an external joint torques observer for the implementation of an outer sensorless compliance controller. More in detail, exploiting the resulting position-controlled robot dynamics, an Extended Kalman Filter (EKF) is proposed to estimate the external joint torques. Exploiting such an estimation, an outer impedance controller can be designed, providing a position/velocity reference to the inner position controller. The described approach has been validated with experiments on a Franka EMIKA panda robot. A human operator interacts with the controlled robot, applying external wrenches (i.e., both Cartesian forces and torques). The resulting external joint torques are estimated making use of the proposed EKF, comparing the achieved results with the signals provided by the joint torque sensors of the Franka EMIKA panda robot (measurements used as a baseline for validation purposes). Experimental results show the capabilities of the proposed control framework in estimating the applied external joint torques while implementing a position control-based compliance controller.