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

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

21 Aug 2019arXiv:1908.08031links table onlyarchive 2025-07-28

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

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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.

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UWRobotLearning/WheeledLab mentioned on GitHubpytorchNOASSERTION report

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