Proprioceptive Navigation, Slip Estimation and Slip Control for Autonomous Wheeled Mobile Robots

Abstract

For a two-wheeled differentially driven mobile robot a navigation and slip control algorithm is developed. The presented concept for purely proprioceptive navigation combines state estimation via extended Kalman filter from inertial sensor data (i.e. gyro and acceleration sensors) and odometric measurements (i.e. wheel angular encoders). The advantages of both types of sensors are exploited by selective mixing. Tangential slip detection and side-slip angle measurement enable slip control by transiently overriding a pre-planned trajectory. Experimental results demonstrating the performance of the proposed system are presented