Fuzzy logic obstacle avoidance by a NAO robot in unknown environment

In the current scenario, among all robots, humanoid robots are of greater importance due to their adaptability to human environment and human-like appearance. Obstacle avoidance is a crucial task for mobile robots and especially for humanoid robots. In this paper, an obstacle avoidance method based on fuzzy inference system is developed. The proposed system is tested on a real humanoid robot NAO V6. The results show that our method is more efficient than the default obstacle avoidance system of our humanoid robot and that our system takes into account several possible directions. Future developments will take into account these results with other systems in order to obtain an autonomous robot in terms of navigation.