Continuous Humanoid Locomotion over Uneven Terrain using Stereo Fusion

For humanoid robots to fulfill their mobility potential they must demonstrate reliable and efficient locomotion over rugged and irregular terrain. In this paper we present the perception and planning algorithms which have allowed a humanoid robot to use only passive stereo imagery (as opposed to actuating a laser range sensor) to safely plan footsteps to continuously walk over rough and uneven surfaces without stopping. The perception system continuously integrates stereo imagery to build a consistent 3D model of the terrain which is then used by our footstep planner which reasons about obstacle avoidance, kinematic reachability and foot rotation through mixed-integer quadratic optimization to plan the required step positions. We illustrate that our stereo imagery fusion approach can measure the walking terrain with sufficient accuracy that it matches the quality of terrain estimates from LIDAR. To our knowledge this is the first such demonstration of the use of computer vision to carry out general purpose terrain estimation on a locomoting robot - and additionally to do so in continuous motion. A particular integration challenge was ensuring that these two computationally intensive systems operate with minimal latency (below 1 second) to allow re-planning while walking. The results of extensive experimentation and quantitative analysis are also presented. Our results indicate that a laser range sensor is not necessary to achieve locomotion in these challenging situations.