Stair climbing for humanoid robots using stereo vision

Abstract

For the fully autonomous navigation in a 3 dimensional world, a humanoid robot must be capable of stepping up and down staircases and other obstacle where a sufficient large flat surface can support the robot's feet. This paper presents methods for the recognition of stairs and a control architecture that enable the humanoid robot QRIO to safely climb up and down in its environment The approach is based on data captured by a stereo vision system and segmented into planar surfaces. From the segmented planes, stairs that can be climbed by the robot are extracted and fed to a control system which decides the action to be taken next. Experimental results on a staircase as well as climbing up and down a sill are presented.