Developing Planning and Reactive Control for a Hexapod Robot

Abstract

We have designed an architecture that allows a gait planner to effectively control primitive walking behaviors. The behaviors ensure safe and efficient walking, even without planning; the addition of planning improves performance in rough terrain by allowing the robot to anticipate changes in its gait. We have implemented our approach and demonstrated it on a real robot, Dante II, and on a simulated hexapod with more complex kinematics. With the hexapod we can produce a variety of gaits and stably switch among them. We have attained performance improvement by using narrowly focused planning to guide behavior.