Skip to content
RobothecaBeta
Log in

6-DOF Robotic Arm

An open-source 6-degree-of-freedom robotic arm designed for simulation, kinematics research, and reinforcement learning-based end-effector control.

  • Robot arm
  • No license: all rights reserved by the creator
  • Work in progress
  • Works with AI
  • 3D model (URDF)
  • 3D printable

Suggested by Robotheca, created by @nanshanbot (opens in a new tab), from github.com/nanshanbot/ARM (opens in a new tab). Pinned to commit edb0ca5 (opens in a new tab).

Fork on GitHub (opens in a new tab)Download the files at this commit (.zip)
Hardware license
No license
Software license
No license
Commercial use
Unknown

No license is stated for part of this robot.

The creator chose the hardware and software licenses on Robotheca; the repository has no license file for them yet.

Photo and 3D model

This repository has no photo of the robot yet.
Try it in the browser

3D model loaded from the original files on GitHub at edb0ca5, under NONE. View the original files from GitHub (3.3 MB) (opens in a new tab)

Degrees of freedom
6
Weight
0.13 m

What it can do

Written by Robotheca from the project's documents.

  • Simulates a 6-axis robotic arm in MuJoCo
  • Provides URDF model for ROS or other robot simulators
  • Trains and tests reinforcement learning policies for end-effector position control
  • Supports PPO algorithm via Stable-Baselines3
  • Visualizes arm movements in MuJoCo viewer
  • Defines 6-dimensional action space for joint angle targets
  • Observes 9-dimensional state including joint angles and end-effector position
  • Reaches target positions within a 0.005 meter tolerance

Works with AI

Found by Robotheca in the project's files at commit edb0ca5, 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. 1Prepare 3D printable parts and materials
  2. 2Assemble mechanical structure using CAD files
  3. 3Set up simulation environment (MuJoCo/URDF)
  4. 4Install Python dependencies and environment
  5. 5Run MuJoCo demonstration for validation
  6. 6Train reinforcement learning model (optional)
  7. 7Test and validate the robotic arm

The creator's guide is written in Chinese. It has no license, so all rights stay with the creator: Robotheca doesn't show it here or translate it, and gives its own notes about the robot instead.

Read the creator's guideAsk the creator on GitHub (opens in a new tab)