Vision Based Tracking of Moving Target in an Autonomous Ground Vehicle Framework

This paper proposes a vision-based algorithm to autonomously track a moving target with an autonomous ground vehicle. The proposed approach, which is to estimate the target’s position and orientation, is built on a robust colour based tracker using the Continuously Adaptive Mean Shift (CAMShift) algorithm. The object tracker can handle occlusions, lighting and environment effects in a single framework when combined with Multiple Kalman Filters. The information is then used from the visual tracker to control the position and yaw angle of the UAV in order to track the object and keep it in the field of view. The system is practically implemented and tested using the Arduino platform and a cheap low cost web based camera.