Multi-agent System for non-Holonomic Racing
This is the main repository for MuSHR.
Components are listed below. Note not all components are installed by default. For install and running various components we recommend following our tutorials also individually linked with each component:
mushr_docs: Install and hardware related docs. Component documentation found with each component
mushr_base: Scripts that ties all mushr components together.
mushr_sim: MuSHR's main simulator
mushr_mujoco_ros: MuSHR's mujoco simulator.
gym-donkeycar: MuSHR version of the Donkeycar simulator
mushr_hardware: launchfiles for running the car and location for installed hardware packages
mushr_description: Official meshes, stl files, and urdf's for each mushr platform. Also contains description of kinematic car model
mushr_cad: CAD files for all versions of the MuSHR car
push_button_utils: ROS node interface for front bumper
vesc: Code for communicating with the MuSHR car's VESC
ydlidar: Package that contains all code for the laser scanner
Realsense: External package for interfacing withe realsense camera
Utils and Development Tools
devtools: Development tools for linting and contributing to MuSHR
mushr_utils: install scripts, rviz setup files, and other utils for running various tasks
mushr_pf: The MuSHR particle filter used for localization in a known map.
mushr_pf.jl: Another MuSHR particle filter written in julia
mushr_rhc: The MuSHR receding horizon controller for navigation in a known map.
mushr_gp: The MuSHR global planner, for planning in a known map.
mushr-dl: A deep learning stack for reinforcement learning in the donkey sim
How do I get started?!
Visit our website! We have an ever-growing list of tutorials and build instructions there.
Who can use MuSHR?
This project is intended for students and researchers at the undergraduate and graduate level, but that doesn't mean you can't do it! We welcome motivated high school students, and makers to try out the platform too. You will need familiarity with the linux terminal, python, and general building skills. No soldering skills are required to build the platform.
This project is from the Personal Robotics Lab at the University of Washington Paul G. Allen School of Computer Science.