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Biped humanoid robots have been developed to successfully perform human-like locomotion. Based on the use of well-developed locomotion control systems, humanoid robots are further expected to achieve high-level intelligence, such as vision-based obstacle avoidance navigation. To provide standard obstacle avoidance navigation problems for autonomous humanoid robot researches, the HuroCup League of Federation of International Robot-Soccer Association (FIRA) and the RoboCup Humanoid League defined the conditions and rules in competitions to evaluate the performance. In this paper, the vision-based obstacle avoidance navigation approaches for humanoid robots were proposed in terms of combining the techniques of visual localization, obstacle map construction and artificial potential field (APF)-based reactive navigations. Moreover, a small-size humanoid robot (HuroEvolutionJR) and an adult-size humanoid robot (HuroEvolutionAD) were used to evaluate the performance of the proposed obstacle avoidance navigation approach. The navigation performance was evaluated with the distance of ground truth trajectory collected from a motion capture system. Finally, the experiment results demonstrated the effectiveness of using vision-based localization and obstacle map construction approaches. Moreover, the APF-based navigation approach was capable of achieving smaller trajectory distance when compared to conventional just-avoiding-nearest-obstacle-rule approach.

This paper presents the design and implementation of fuzzy controller based subsumption behavior architecture for controlling an autonomous robotic wheelchair. Behaviors of autonomous robotic wheelchair generally developed with one or more basic behaviors such as goal seeking, wall following, obstacle avoidance and finding target based on different environmental conditions. Therefore, to maximize the navigation performance, fuzzy controller based subsumption behavior architecture is proposed as a sensor fusion algorithm and to find most suitable robotic wheelchair behavior according to environment condition. The arbitrate competition is used to decide which behavior controller has a higher priority, then robotic wheelchair can be controlled by the highest priority behavior during the robotic wheelchair movement towards the goal or target. In order to verify our approach, a robotic wheelchair is controlled with a microcontroller for motion control and sensors information acquisition, personal computer connects to a web-camera for visual localization. The experiment of simulation and test results were presented to show the validity of the proposed method.