A Method for Robustness Improvement of Robot Obstacle Avoidance Algorithm

The robustness of obstacle avoidance algorithm is one of the important factors to successful applications of mobile robot systems. The sonar ring is used widely for autonomous mobile robot obstacle avoidance. This paper first analyzes the robustness of the existing obstacle avoidance algorithms based on sonar ring, indicates that the certainty grid method for obstacle representation is helpful to the robustness improvement of obstacle avoidance algorithms, but its effect is limited, it also has many disadvantages. By the simulation of two typical obstacle avoidance algorithms, the damage of interfered sonar data is revealed. Then the kinematics model of obstacle avoidance is built, Kalman filter which can restrain divergence is designed for interfered sonar data. Sonar data is used by obstacle avoidance algorithm after filtering. By the simulation contrast of the two obstacle avoidance algorithms, the effect of the Kalman filter for robustness improvement of obstacle avoidance algorithms is testified. Finally, the effect of the Kalman filter for eliminating noises in sonar data and for robustness improvement of obstacle avoidance algorithms is verified by experiments in two different situation.