A Distributed Local-Leg Feedback Algorithm for Robust Walking on Uneven Terrain

Abstract

Legged animals can traverse significantly more of the Earth's land mass than man-made wheeled and tracked vehicles~\\cite{Anonymous67}. Their impressive mobility is largely due to multiple dexterous legs and the robust algorithms that coordinate and control them. A legged animal such as a squirrel can exhibit multiple locomotion modes such as walking, running and jumping and also multiple gaits or leg phase timings within each mode. A robot that could mimic this level of robust locomotion would be highly useful for planetary exploration, military reconnaissance, and time-critical search and rescue in cluttered or collapsed buildings.\nA number of biological studies on animal walking have provided information concerning the underlying control system. Studies in insect walking have revealed a distributed local-leg control that generates quasi-rhythmic movement by sensing the environment using local feedback loops. Ground reaction forces produced by an insect during walking and running, along with joint angles, have been recorded by various studies. The primary goal of this research is to develop a distributed local-leg control algorithm to generate walking behaviors on uneven terrain using local force feedback. The intended purpose of this research is to pursue a biologically-inspired control algorithm that can be used as a scientific tool to study walking and provide a better understanding of local-leg control.\nControl of a multi-jointed robot system has traditionally been done using position control. But as the number of degrees of freedom in systems started increasing, position control of each actuator using a centralized controller became cumbersome. The control of a walking robot is a more complex problem as stability also becomes an issue. Much research has been concentrated towards creating rhythmic or quasi-rhythmic movements which can be used for walking in predictable environments. However, walking on uneven terrain requires one to incorporate different issues, such as but not limited to, the mechanical properties of the leg, coordination between legs, as well as higher level decisions based on external information and internal body states. Much of the current research in legged robots is directed towards sensing the terrain so that the walking sequence of the robot can be pre-determined. This requires a large array of sensors, off-line as well as in real-time, to accurately sense the terrain increasing the cost and complexity of the robot. Even if the body path and footholds are planned, a real-time module is required to handle small perturbations and slips adding to the complexity. Like animal walking, using force feedback can greatly improve walking behavior in a robot. However, due to the unreliable nature of force sensors, no other control algorithm for walking has been able to use continuous force feedback for walking on uneven terrain.\nThe distributed local-leg controller developed in this research, called Force Threshold-based Position (FTP) controller, is able to generate walking behaviors robust to terrain elevations without using visual sensors, a priori terrain information, inertial sensing, or inter-leg communication. The controller uses local force feedback to control each leg and is, therefore, very responsive to terrain changes when compared to a centralized controller arbitrating all of the joint positions in a high degree of freedom system. The controller is implemented with gait phasing dictated by a static timer. By integrating force feedback with position control, the FTP controller combines the advantages of position control with robustness to uneven terrain. This work provides the minimum interaction needed between joints or legs for the robot to navigate a rugged terrain. This work provides insight into the role of active elements in the local leg feedback controller that allow for responsiveness over uneven terrain, and can be used to reveal the underlying structure insects use to generate th