LeVR: A Modular VR Teleoperation Framework for Imitation Learning in Dexterous Manipulation

We introduce LeVR, a modular software framework designed to bridge two critical gaps in robotic imitation learning. First, it provides robust and intuitive virtual reality (VR) teleoperation for data collection using robot arms paired with dexterous hands, addressing a common limitation in existing systems. Second, it natively integrates with the powerful LeRobot imitation learning (IL) framework, enabling the use of VR-based teleoperation data and streamlining the demonstration collection process. To demonstrate LeVR, we release LeFranX, an open-source implementation for the Franka FER arm and RobotEra XHand, two widely used research platforms. LeFranX delivers a seamless, end-to-end workflow from data collection to real-world policy deployment. We validate our system by collecting a public dataset of 100 expert demonstrations and use it to successfully fine-tune state-of-the-art visuomotor policies. We provide our open-source framework, implementation, and dataset to accelerate IL research for the robotics community.

BiDexHand: Design and Evaluation of an Open-Source 16-DoF Biomimetic Dexterous Hand

Achieving human-level dexterity in robotic hands remains a fundamental challenge for enabling versatile manipulation across diverse applications. This extended abstract presents BiDexHand, a cable-driven biomimetic robotic hand that combines human-like dexterity with accessible and efficient mechanical design. The robotic hand features 16 independently actuated degrees of freedom and 5 mechanically coupled joints through novel phalange designs that replicate natural finger motion. Performance validation demonstrated success across all 33 grasp types in the GRASP Taxonomy, 9 of 11 positions in the Kapandji thumb opposition test, a measured fingertip force of 2.14\,N, and the capability to lift a 10\,lb weight. As an open-source platform supporting multiple control modes including vision-based teleoperation, BiDexHand aims to democratize access to advanced manipulation capabilities for the broader robotics research community.