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RC WheelLeg

A 16-degree-of-freedom wheeled-legged robot designed for Robocon obstacle courses, combining reinforcement learning, MuJoCo simulation, and real-world deployment.

  • Wheeled
  • Open source
  • Works with AI
  • ROS 2
  • 3D printable

Suggested by Robotheca, created by @zeitvex (opens in a new tab), from github.com/zeitvex/RC_WheelLeg (opens in a new tab). Pinned to commit 1bc9aa5 (opens in a new tab).

Hardware license
MIT (opens in a new tab)
Software license
MIT (opens in a new tab)
Commercial use
Allowed

This repository contains executable files that Robotheca doesn't check. Only run them if you trust the creator.

Which files (34 scripts)

Photo and 3D model

RC WheelLeg, photo from its repository
Photo:@zeitvex (opens in a new tab)MITsource file (opens in a new tab)

3D preview converted from github.com/zeitvex/RC_WheelLeg at 1bc9aa5, under MIT. View the original files from GitHub (35.3 MB) (opens in a new tab)

Degrees of freedom
16

What it can do

Written by Robotheca from the project's documents.

  • Moves on four wheel-legs with 16 DOF using reinforcement learning policies
  • Runs 50 Hz policy inference and 200 Hz motor control loop on Jetson Orin Nano
  • Supports ROS 2 Navigation2 stack for waypoint navigation and mapping
  • Provides safety monitoring, emergency stop and zero-command hold logic
  • Publishes joint states, IMU data and runtime diagnostics over ROS 2 topics
  • Accepts velocity commands via /cmd_vel for teleoperation or navigation

Works with AI

Found by Robotheca in the project's files at commit 1bc9aa5, its robot.yaml and Robotheca's notes on its documents. Never guessed; Robotheca doesn't run the code.

Bill of materials

This repository has no parts list Robotheca can read yet.

Build guide

The creator's steps, each with its instructions.

  1. 1Review project documentation and BOM
  2. 23D print mechanical parts
  3. 3Assemble mechanical structure
  4. 4Build and test hardware (PCB, sensors, actuators)
  5. 5Flash firmware to microcontrollers
  6. 6Set up software environment (MuJoCo, mjlab, ROS 2)
  7. 7Train reinforcement learning policy in simulation
  8. 8Validate policy with Sim2Sim
  9. 9Deploy policy to real robot (Python Sim2Real or ROS 2/C++)
  10. 10Perform safety checks and calibration
  11. 11Conduct real-world testing and tuning

The guide appears here as you scroll.

Guide by @zeitvex (README.md), under MIT. The English translation is by Robotheca, shared under the same license.

More guides

Wiring and electronics

Notes written by Robotheca from the project's documents.

Main parts

  • Jetson Orin Nano 8G as main computer
  • 16 RS02 actuators (12 for joints, 4 for wheels)
  • Odin1 integrated IMU and sensors via USB
  • Two CAN interfaces (CAN0, CAN1) for motor communication
  • Peak CAN or USB-to-CAN adapter for CAN bus
  • Peak System CAN interfaces for motor control

Connections

  • CAN0 and CAN1 connected to motor drivers at 1 Mbps
  • Odin1 USB connected to Jetson Orin Nano for IMU and sensor data
  • Jetson Orin Nano provides power to Odin1 over USB
  • Motor power and control lines routed through CAN bus and USB