An Algorithm for Automatic Guided Vehicle Based on Machine Vision and DR

This paper designs a novel algorithm for automatic guided vehicle. The algorithm uses the CCD in front of the vehicle to identify the routing indicator and to calculate the yaw angle from track. It applies the odometer to get vehicle displacement. The DR algorithm can provide the vehicle direction and position from the yaw angle and displacement. Machine vision guidance can identify and track the routing indicator. It uses the adaptive fuzzy feedback to identify faster and better, further uses a novel simple arithmetic to reduce picture jitter. The system used this algorithm can avoid the position error accumulated with time as general DR and cost lower. Plenty of examinations prove that the algorithm can efficiently improve the position precision