Robust contact force estimation for robot manipulators in three-dimensional space

Abstract

Information on contact forces in robot manipulators is indispensable for fast and accurate force control. Instead of expensive force sensors, estimation algorithms for contact forces have been widely developed. However, it is not easy to obtain the accurate values due to uncertainties. In this article, a new robust estimator is proposed to estimate three-dimensional contact forces acting on a three-link robot manipulator. The estimator is based on the extended Kalman filter (EKF) structure combined with a Lyapunov-based adaptation law for estimating the contact force. In contrast to the conventional EKF the new estimator is designed such that it is robust to the deterministic uncertainties such as the modelling error and the sensing bias. The performance of the proposed estimator is evaluated through simulations of a robot manipulator and demonstrates robustness in estimating the contact force. The estimation results show that it can be potentially used to replace the expensive force sensors in robot applications.