Obstacle avoidance for mobile robot based on improved dynamic window approach

Abstract

The dynamic window approach has the drawback that it may result in local minima and nonoptimal motion decision for obstacle avoidance because of not considering the size constraint of a mobile robot. Thus, an improved dynamic window approach is proposed, which takes into account the relation between the size of the mobile robot and the free space between obstacles. A laser range finder is employed to improve the ability of sensing and prediction of the environment, in order to avoid being trapped in a U-shaped obstacle, such as a box canyon. By applying the proposed method, the local minima problem can be solved and the optimal path can be obtained. The effectiveness and superiority is proven by theoretic analysis and simulations.