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MuSHR: A Low-Cost, Open-Source Robotic Racecar for Education and Research

Siddhartha S Srinivasa, Patrick Lancaster, Johan Michalove, Matt Schmittle, Colin Summers, Matthew S. Rockett, Joshua R. Smith, Sanjiban Choudhury, Christoforos Mavrogiannis, Fereshteh Sadeghi

Year
2019
Citations
45
Access
Open access

Abstract

We present MuSHR, the Multi-agent System for non-Holonomic Racing. MuSHR is a low-cost, open-source robotic racecar platform for education and research, developed by the Personal Robotics Lab in the Paul G. Allen School of Computer Science & Engineering at the University of Washington. MuSHR aspires to contribute towards democratizing the field of robotics as a low-cost platform that can be built and deployed by following detailed, open documentation and do-it-yourself tutorials. A set of demos and lab assignments developed for the Mobile Robots course at the University of Washington provide guided, hands-on experience with the platform, and milestones for further development. MuSHR is a valuable asset for academic research labs, robotics instructors, and robotics enthusiasts.

Keywords

RoboticsDocumentationArtificial intelligenceRobotOpen sourceHolonomicEngineering managementEngineeringComputer scienceHuman–computer interaction

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