A Framework for Obstacles Avoidance of Humanoid Robot using Stereo Vision

In this paper, we propose a framework for multiple moving obstacles avoidance strategy using stereo vision for humanoid robot in indoor environment. We assume that this model of humanoid robot is used as a service robot to deliver a cup to customer from starting point to destination point. We have successfully developed and introduced three main modules to recognize faces, to identify multiple moving obstacles and to initiate a maneuver. A group of people who are walking will be tracked as multiple moving obstacles. Predefined maneuver to avoid obstacles is applied to robot because the limitation of view angle from stereo camera to detect multiple obstacles. The contribution of this research is a new method for multiple moving obstacles avoidance strategy with Bayesian approach using stereo vision based on the direction and speed of obstacles. Depth estimation is used to obtain distance calculation between obstacles and the robot. We present the results of the experiment of the humanoid robot called Gatotkoco II which is used our proposed method and evaluate its performance. The proposed moving obstacles avoidance strategy was tested empirically and proved effective for humanoid robot.