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.

翻译：我们提出了MuSHR——非完整约束赛车多智能体系统。MuSHR是由华盛顿大学保罗·G·艾伦计算机科学与工程学院的个人机器人实验室开发的一款低成本、开源机器人赛车平台，致力于通过提供详细的开源文档和自助教程，推动机器人技术的民主化进程。针对华盛顿大学移动机器人课程设计的系列演示与实验作业，为用户提供平台操作的引导式实践体验及进阶开发路径。MuSHR对学术研究实验室、机器人教学工作者及机器人爱好者均具有重要实用价值。