Quadrupedal Walking over Complex Terrain with a Quasi-Direct Drive Actuated Robot

Abstract

In this paper, we present our approach to achieve autonomous walking over complex terrain on the quadrupedal robot, LLAMA. LLAMA is a prototype robot designed by NASA Jet Propulsion Lab as part of the Army Research Laboratory’s Robotics Collaborative Technology Alliance. One of the major objectives of this robot is to be capable of traversing complex terrain autonomously to enable operating alongside a human squadron. This goal requires the robot to be capable of identifying practical footholds according to the environment, which may be sparse, and using these for walking. To accomplish this end, we first introduce two new contact planners. One is based on either desired body path plans; the other an A* graph-search based planner that find contacts over rough terrain given the environmental constraints. We then plan a dynamic trajectory using a custom Divergent Component of Motion planner, which is tracked using a whole-body inverse-dynamics control framework. We also introduce new methods for maintaining balance by adjusting step position and timing. We additionally discuss our approach for contact detection without the use of force sensors. We highlight the results in several experiments, both in our laboratory and at the RCTA Capstone Event at the Camp Lejeune Marine Corps base. We conclude with a discussion of these results, specific implementation problems, and lessons learned when developing such a control architecture on a quadruped.

Lessons Learned from two iterations of LLAMA, an Electrically Powered, Dynamic Quadruped Robot

“…To this end, a custom control system that models the environment then plans and executes specific footholds was designed. This system is described very briefly here, and more completely in a companion paper (Griffin et al, 2021). The deliberative control system first models the environment by extracting planar regions from a lidar point cloud.…”

“…Left: Image of a rock field set up at Camp Lejeune. Right: Using the deliberative controller detailed in a companion paper(Griffin et al, 2021), the robot used lidar data to create a simplified model of the environment, then planned each footstep to traverse the obstacles using an A* planner. The robot then successfully walked over the blocks, up the curb, and onto the inclined concrete slope on the other side.…”

Enhancement of humanoid robot locomotion on slippery floors using an adaptive controller

“…The strategy described in this paper is founded on an implementation and adaptation of a DCM-based control architecture. The DCM concept has been applied to various types of robots, including bipeds [9][10][11][12][13][14], quadrupeds [15,16], and exoskeletons [17,18], and has been shown to be effective in achieving stable and dynamic locomotion. It has also been used in applications such as prosthetics and rehabilitation robotics, where maintaining balance and stability are critical for safe and effective movement.…”