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Official Github repository for "PAPRLE: Plug-And-Play Robotic Limb Environment A Modular Ecosystem for Robotic Limbs"

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PAPRLE (Plug-And-Play Robotic Limb Environment)

Overview

concept

This repository provides source code for the teleoperation system of PAPRLE.

PAPRLE supports diverse follower robot configurations and also diverse leader configurations.

For installation, please refer to Installation.

Supported Environment

  • Mujoco
  • Isaacgym
  • ROS1 (Gazebo or Hardware)
  • ROS2 (Gazebo or Hardware)

Supported Robots (Follower)

  • Using PAPRAS, we can build various configurations of robotic arms. PAPRLE is designed to support such diverse configurations, and below are the configurations we have tested so far:
    • papras_6dof : One-arm 6-DOF PAPRAS
    • papras_7dof : One-arm 7-DOF PAPRAS
    • papras_6dof_2arm_table : Dual-arm 6-DOF PAPRAS on Table
    • papras_7dof_2arm_table : Dual-arm 7-DOF PAPRAS on Table
    • papras_orthrus : Dual-arm 7-DOF PAPRAS on Spot (Orthrus)
    • papras_stand : Dual-arm 7-DOF PAPRAS on Stand

PAPRAS is a fully open-source robotic arm, and you can find the CAD files and other detailed information on the site. For more information about PAPRAS, please visit this site.

  • Also, PAPRLE has been tested with other robots.
    • G1 : Unitree G1
    • OpenManipulator-Y : OpenManipulator-Y from Robotis
    • PiPER: PiPER

Supported Devices (Leader)

  • Keyboard
  • Puppeteer
  • VisionPro
  • Joycon
  • PS5 DualSense

Citation

This repository is based on PAPRLE.
If you find this code useful in your research, please consider citing:

@ARTICLE{kwon2026paprle,
  author={Kwon, Obin and Yamsani, Sankalp and Myers, Noboru and Taylor, Sean and Hong, Jooyoung and Park, Kyungseo and Alspach, Alex and Kim, Joohyung},
  journal={IEEE Robotics & Automation Magazine}, 
  title={PAPRLE: Plug-And-Play Robotic Limb Environment: A Modular Ecosystem for Robotic Limbs}, 
  year={2026},
  volume={},
  number={},
  pages={2-12},
  keywords={Robots;Limbs;Kinematics;Input devices;Humanoid robots;Automation;Artificial intelligence;Force feedback;End effectors;Wrist},
  doi={10.1109/MRA.2025.3647246}}

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