This paper presents Stanford Doggo, a quasi-direct-drive quadruped capable of dynamic locomotion. This robot matches or exceeds common performance metrics of state-of-the-art legged robots. In terms of vertical jumping agility, a measure of average vertical speed, Stanford Doggo matches the best performing animal and surpasses the previous best robot by 22%. An overall design architecture is presented with focus on our quasi-direct-drive design methodology. The hardware and software to replicate this robot is open-source, requires only hand tools for manufacturing and assembly, and costs less than $3000.
@article{arxiv.1905.04254,
title = {Stanford Doggo: An Open-Source, Quasi-Direct-Drive Quadruped},
author = {Nathan Kau and Aaron Schultz and Natalie Ferrante and Patrick Slade},
journal= {arXiv preprint arXiv:1905.04254},
year = {2019}
}
Comments
Accepted to the IEEE International Conference on Robotics and Automation 2019