Obstacle avoidance in person following for vision-based autonomous land vehicle guidance using vehicle location estimation and quadratic pattern classifier

Abstract

An obstacle avoidance method for use in person following for vision-based autonomous land vehicle (ALV) guidance is proposed. This method is based on the use of vehicle location estimation and a quadratic pattern classifier, and aims to guide the ALV to follow a walking person in front by navigating along a derived collision-free path. Before generating the collision-free path, the person's location is obtained from extracted objects in the image by a person detection method. The object closest to a predicted person location is regarded as the followed person and the remaining objects are regarded as obstacles. The collision-free navigation path is designed for ALV guidance in such a way that the ALV not only can keep following the person but also can avoid collision with nearby obstacles. The navigation path results from a quadratic classifier that uses the vehicle and all of the objects in the image as input patterns. A turn angle is then computed to drive the ALV to follow the navigation path. Successful navigation sessions confirm the feasibility of the approach.