Walking navigation system of humanoid robot using stereo vision based floor recognition and path planning with multi-layered body image

To realize humanoid robots in unknown environment, sensor based navigation system is required as one of an essential function. This paper describes vision-based navigation system for humanoid robots, which has following features: 1) To recognize floor regions from a view of vision of a humanoid robot in unknown environment, we utilized existing technique called Plane Segment Finder, which is able to extract arbitrary planner surface regions from depth image. 2) Path planning for wheeled robots usually models a robot as a 2D circle, however path planning system for humanoid robot requires capable of modeling a robot as a 3D cylinder model, convex hull model, rigid model and so on, according to a situation such as a robot carries a large object or a robot opens its arms. Finally, we show a humanoid robot HOAP-1 with enhanced stereo vision system for navigation task and a result of path planning using generated local map through stereo vision system which uses real images as an input.