Linear Policies are Sufficient to Enable Low-Cost Quadrupedal Robots to Traverse Rough Terrain
Maurice Rahme, Ian Abraham, Matthew L. Elwin, Todd D. Murphey
Abstract
The availability of inexpensive 3D-printed quadrupedal robots motivates the development of learning-based methods compatible with low-cost embedded processors and position-controlled hobby servos. In this work, we show that a linear policy is sufficient to modulate an open-loop trajectory generator, enabling a quadruped to walk over rough, unknown terrain, with limited sensing. The policy is trained in simulation using randomized terrain and dynamics and directly deployed on the robot. We show that the resulting controller can be implemented on resource-constrained systems. We demonstrate the results by deploying the policy on the OpenQuadruped, an open-source 3D-printed robot equipped with hobby servos and an embedded microprocessor.
BibTeX
@inproceedings{iros2021_linearpoliciesar,
title = {Linear Policies are Sufficient to Enable Low-Cost Quadrupedal Robots to Traverse Rough Terrain},
author = {Maurice Rahme and Ian Abraham and Matthew L. Elwin and Todd D. Murphey},
booktitle = {IROS 2021},
year = {2021}
}