Traction estimation and control for Mobile Robots using the wheel slip velocity

Abstract

Mobile robots are used to venture through types of environments, at low wheel speeds, where wheel slip is a threat. We present a unique traction estimation algorithm for low speed applications that estimates traction loss by measuring the wheel slip velocity. We also propose a modified Kalman Filter that fuses a system model of a DC motor with an estimate of the disturbances acting on the system model. Using the wheel slip velocity we propose a traction control law for low speed applications that provides the ability of tracking a desired reference while mitigating traction loss.