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

2025-07-07

AI Summary

To address rigidity in robotic limb configurations, challenges in multi-device coordinated control, and latency in force feedback within embodied AI research, this paper proposes a modular robotic limb ecosystem. Methodologically, it introduces plug-and-play manipulation units coupled with a bidirectional, low-latency communication architecture enabling real-time force feedback in both joint and task spaces; it further integrates multimodal inputs—including VR systems and game controllers—to achieve plug-and-play bilateral teleoperation between heterogeneous master devices and slave robots. The key contributions are: (i) the first open-source, hardware-software-integrated modular ecosystem, significantly enhancing configuration flexibility, cross-platform compatibility, and haptic fidelity; and (ii) empirical validation of system stability and scalability across diverse teleoperation scenarios, establishing a reproducible foundational platform for data-driven learning and adaptive control in embodied AI.

Technology Category

• Intelligent Robots: Embodied AI
• Humans and AI: Interaction Techniques and Devices
• Multiagent Systems: Agent Communication

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications

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

Problem

• Enables flexible placement and control of robotic limbs
• Supports versatile teleoperation with various input devices
• Facilitates modular design for scalable data collection

Innovation

• Modular ecosystem for flexible robotic limbs
• Pluggable puppeteer device for easy configuration
• Supports joint-space and task-space control