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

TL;DR

MuSHR is an affordable, open-source robotic racecar designed for educational and research purposes, aiming to democratize robotics and facilitate hands-on learning through comprehensive documentation and demos.

Contribution

This paper introduces MuSHR, a low-cost, open-source racing platform that supports education and research, with detailed tutorials and community resources for widespread adoption.

Findings

Successfully deployed in university courses for hands-on robotics education

Provides a cost-effective platform accessible to diverse users

Supports research and development in multi-agent robotic racing

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.