PAPRLE (Plug-And-Play Robotic Limb Environment): A Modular Ecosystem for Robotic Limbs

TL;DR

PAPRLE is a modular, open-source ecosystem enabling flexible, scalable control and configuration of robotic limbs for diverse teleoperation scenarios, supporting real-time feedback and community-driven development.

Contribution

It introduces a versatile, plug-and-play platform for robotic limbs that supports various control interfaces and configurations, advancing research and application in embodied AI and teleoperation.

Findings

Validated across multiple real-world setups

Supports bilateral teleoperation with force feedback

Enables novel limb arrangements and scalable data collection

Abstract

We introduce PAPRLE (Plug-And-Play Robotic Limb Environment), a modular ecosystem that enables flexible placement and control of robotic limbs. With PAPRLE, a user can change the arrangement of the robotic limbs, and control them using a variety of input devices, including puppeteers, gaming controllers, and VR-based interfaces. This versatility supports a wide range of teleoperation scenarios and promotes adaptability to different task requirements. To further enhance configurability, we introduce a pluggable puppeteer device that can be easily mounted and adapted to match the target robot configurations. PAPRLE supports bilateral teleoperation through these puppeteer devices, agnostic to the type or configuration of the follower robot. By supporting both joint-space and task-space control, the system provides real-time force feedback, improving user fidelity and physical interaction awareness. The modular design of PAPRLE facilitates novel spatial arrangements of the limbs and enables scalable data collection, thereby advancing research in embodied AI and learning-based control. We validate PAPRLE in various real-world settings, demonstrating its versatility across diverse combinations of leader devices and follower robots. The system will be released as open source, including both hardware and software components, to support broader adoption and community-driven extension. Additional resources and demonstrations are available at the project website: https://uiuckimlab.github.io/paprle-pages