A Vision-Based Technique for Vehicle Slip and Velocity Estimation

This paper proposes a novel technique to estimate slips and velocities of an unmanned ground vehicle (UGV). A visual odometry sensor looking down the terrain surface is employed to measure the motion of the UGV, by tracking features selected from the terrain surface. The visual odometry sensor can provide motion information even when the terrain surface contains no distinctive features. A sliding mode observer (SMO) based-on a kinematic model is designed to deal with noise and uncertainty of the measurements from the visual odometry sensor, and simultaneously estimate the slip and velocity vectors of the UGV. The non-GPS slip and velocity estimation technique is independent of terrain parameters and robust to noise and uncertainty. Experimental results are given to show that the technique has good potential for vehicle slip and velocity estimation.