Stereo-based obstacle avoidance in indoor environments with active sensor re-calibration

We present a stereo-based obstacle avoidance system for mobile vehicles. The system operates in three steps. First, it models the surface geometry of the supporting surface and removes the supporting surface from the scene. Next, it segments the remaining stereo disparities into connected components in image and disparity space. Finally, it projects the resulting connected components onto the supporting surface and plans a path around them. One interesting aspect of this system is that it can detect both positive and "negative" obstacles (e.g. stairways) in its path. The algorithms we have developed have been implemented on a mobile robot equipped with a real-time stereo system. We present experimental results on indoor environments with planar supporting surfaces that show the algorithms to be both fast and robust.