Handroid: Bridging Dexterous Hand and Humanoid
2026-07-17 • Robotics
Robotics
AI summaryⓘ
The authors present Handroid, a small robot that can change its shape between a dexterous hand and a humanoid robot. It uses the same mechanical parts to either perform detailed hand movements or walk and move like a tiny human. They also built software to control both forms, allowing tasks like grasping objects and walking. The authors tested Handroid in various scenarios, showing it can switch forms and perform complex tasks, making it useful for research on robots that can change bodies and learn different skills.
dexterous handhumanoid robotdegrees of freedom (DoF)teleoperationreinforcement learningkinematicslocomotionrobot morphologyin-hand manipulationmotion planning
Authors
Ruogu Li, Chenyang Ma, Sikai Li, Zhenyu Wei, Yunchao Yao, Haochen Shi, C. Karen Liu, Shuran Song, Mingyu Ding
Abstract
Dexterous hands and humanoid robots are typically developed as distinct embodiments: the former enable contact-rich manipulation at the object scale, whereas the latter provide mobility and whole-body interaction in human-centered environments. We introduce \textbf{Handroid}, a desktop-scale dual-embodiment robot that integrates both capabilities within a single reconfigurable platform. Handroid reuses one 27-DoF electromechanical body as either a dexterous hand or a desktop humanoid, measuring 0.33 m in height and 2.05 kg in weight. In the dexterous hand embodiment, 20 DoFs form an anthropomorphic hand closely matching the kinematic structure of the human hand. In the humanoid embodiment, the same articulated modules are reconfigured into a humanoid with a head, arms, and legs, including a 12-DoF lower-limb structure for locomotion and whole-body motion. Handroid further provides a unified control and learning framework supporting hand teleoperation, dexterous grasping, in-hand manipulation, humanoid locomotion, gait generation, and interactive motion authoring. We validate the platform through real-world dexterous manipulation, reinforcement-learning-based locomotion, keyframe motion deployment, and a long-horizon task involving embodiment reconfiguration, locomotion, docking, and dexterous pick-and-place. These results position Handroid as a compact and reproducible platform for advancing morphology-reconfigurable robotics and cross-embodiment robot learning.