A floor and obstacle height map for 3d navigation of a humanoid robot

Abstract With the development of biped robots, systems became able to navigate in a 3 dimensional world, walking up and down stairs, or climbing over small obstacles. We present a method for obtaining a labeled 2.5D grid map of the robot’s surroundings. Each cell is marked either as oor or obstacle and contains a value telling the height of the oor or obstacle. Such height maps are useful for path planning and collision avoidance. The method uses a novel combination of a 3D occupancy grid for robust sensor data interpretation and a 2.5D height map for ne resolution oor values. We evaluate our approach using stereo vision on the humanoid robot QRIO and show the advantages over previous methods. Experimental results from navigation runs on an obstacle course demonstrate the ability of the method to generate detailed maps for autonomous navigation. Index Terms 3D perception and navigation, obstacle avoid-ance, humanoid robot. I