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

Nathan Kau, Aaron P. Schultz, Natalie Ferrante, Patrick Slade

Year
2019
Citations
12

Abstract

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.

Keywords

RobotReplicateComputer scienceFocus (optics)JumpingSoftwareMeasure (data warehouse)SimulationOpen sourceArtificial intelligence

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