ROMay 10, 2019

Stanford Doggo: An Open-Source, Quasi-Direct-Drive Quadruped

arXiv:1905.04254v1136 citationsHas Code
Originality Incremental advance
AI Analysis

This provides an accessible, high-performance platform for robotics research and education, though it is incremental in design methodology.

The paper tackled the challenge of creating a low-cost, open-source quadruped robot capable of dynamic locomotion, resulting in Stanford Doggo matching or exceeding state-of-the-art performance metrics, including surpassing the previous best robot by 22% in vertical jumping agility.

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.

Code Implementations4 repos
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