Abstract: Obstacle avoidance is an important aspect of navigation for autonomous mobile robots. An efficient algorithm of obstacle avoidance was put forward based on multiple objective optimization (MOO) theory. The algorithm gives how to acquire the efficient solution for mobile robots using the multiple objective optimization theory. The method divides the navigation with the given goal into three subbehaviors, which can be changed dynamically according to the current weighting or priority, in order to acquire the most satisfying path or preferred solution at current time. In the end, the experiment shows that the algorithm can improve the security and smoothness of obstacle avoidance efficiently without sacrificing the
robustness of the whole process.

Key words: multiple objective optimization, behavior fusion, deadlock, smoothness of obstacle avoidance