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

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.