Perception-based control for a quadruped walking robot

The progress made so far in the study of legged robots has dealt mostly with the issues of leg coordination, gait control, stability, incorporation of various types of sensors, etc. But what is missing in most of these robots is some perception-based high-level control that would permit a robot to operate intelligently. For the high-level control, a model-based method to recognize a staircase using a single 2D image of a 3D scene is studied. The staircase recognition is achieved by obtaining the pose of a camera coordinate frame which aligns model edges with image edges. The method contains the matching, the pose estimation, and the refinement procedures. A new matching scheme is proposed to reduce the complexity of correspondence search between model and image features. This is accomplished by grouping edges with certain geometric characteristics together. The refinement process uses all matched features to tightly fit the model edges with camera image edges. The resulting recognition is used to guide the robot to climb stairs.