A Vision Based Wheel Slip Estimation Technique for Mining Vehicles

Abstract

Slip plays a vital role in traction control when a mining vehicle traverses over soft soil. This paper presents a vision-based wheel slip estimation technique for mining vehicles. A downward-looking camera is mounted with a special tilted angle to observe both the rotary motion of the wheel and the wheel translatory motion relative to the soil. An optical flow algorithm is developed to estimate the wheel angular velocity and the wheel translatory velocity, by tracking salient features selected from the soil surface and the wheel tire surface separately. The specially orientated camera enables the vision-based algorithm to estimate the wheel slip without wheel odometry information. The proposed technique has been validated on a linear test rig, showing good performance.