UniBiDex: A Unified Teleoperation Framework for Robotic Bimanual Dexterous Manipulation

2026-01-08

arXiv.org

AI Summary

This work proposes the first unified dual-arm teleoperation framework that integrates both virtual reality (VR) and master-slave modalities to address key challenges in heterogeneous input device integration, real-time performance, safety, and coordinated motion. The framework employs a shared control stack to ensure consistent kinematic processing and enforce safety constraints, complemented by a null-space optimization strategy that guarantees collision-free and singularity-avoiding cooperative motion. It enables real-time, contact-rich dexterous manipulation and is accompanied by open-sourced hardware and software to facilitate the collection of high-quality demonstration data. In a long-horizon kitchen organization task comprising five subtasks, the proposed method significantly outperforms strong baselines in task success rate, trajectory smoothness, and robustness.

Technology Category

• Intelligent Robots: Manipulation
• Computer Vision: Multi-modal Vision
• Planning, Routing, and Scheduling: Replanning and Plan Repair

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Web applications in cross-disciplinary domains and verticals such as mixed reality, smart cities, and digital health
• Search and Retrieval-Augmented AI: Vertical and domain-specific search

Abstract

We present UniBiDex a unified teleoperation framework for robotic bimanual dexterous manipulation that supports both VRbased and leaderfollower input modalities UniBiDex enables realtime contactrich dualarm teleoperation by integrating heterogeneous input devices into a shared control stack with consistent kinematic treatment and safety guarantees The framework employs nullspace control to optimize bimanual configurations ensuring smooth collisionfree and singularityaware motion across tasks We validate UniBiDex on a longhorizon kitchentidying task involving five sequential manipulation subtasks demonstrating higher task success rates smoother trajectories and improved robustness compared to strong baselines By releasing all hardware and software components as opensource we aim to lower the barrier to collecting largescale highquality human demonstration datasets and accelerate progress in robot learning.

Problem

• bimanual manipulation
• teleoperation
• dexterous manipulation
• robotic control
• contact-rich tasks

Innovation

• bimanual teleoperation
• nullspace control
• heterogeneous input integration
• contact-rich manipulation
• open-source robotics