Ruka-v2: Tendon Driven Open-Source Dexterous Hand with Wrist and Abduction for Robot Learning

Abstract

Lack of accessible and dexterous robot hardware has been a significant bottleneck to achieving human-level dexterity in robots. Last year, we released Ruka, a fully open-sourced, tendon-driven humanoid hand with 11 degrees of freedom - 2 per finger and 3 at the thumb - buildable for under $1,300. It was one of the first fully open-sourced humanoid hands, and introduced a novel data-driven approach to finger control that captures tendon dynamics within the control system. Despite these contributions, Ruka lacked two degrees of freedom essential for closely imitating human behavior: wrist mobility and finger adduction/abduction. In this paper, we introduce Ruka-v2: a fully open-sourced, tendon-driven humanoid hand featuring a decoupled 2-DOF parallel wrist and abduction/adduction at the fingers. The parallel wrist adds smooth, independent flexion/extension and radial/ulnar deviation, enabling manipulation in confined environments such as cabinets. Abduction enables motions such as grasping thin objects, in-hand rotation, and calligraphy. We present the design of Ruka-v2 and evaluate it against Ruka through user studies on teleoperated tasks, finding a 51.3% reduction in completion time and a 21.2% increase in success rate. We further demonstrate its full range of applications for robot learning: bimanual and single-arm teleoperation across 13 dexterous tasks, and autonomous policy learning on 3 tasks. All 3D print files, assembly instructions, controller software, and videos are available at https://ruka-hand-v2.github.io/ .

Figures (15)

• Figure 1: (A) Ruka-v2 has an integrated 2 DOF decoupled parallel wrist, enabling motion in restricted areas, while also introducing finger abduction/adduction to expand dexterity. (B) Ruka-v2 has a mount attachment that is located at the side of wrist rather than the bottom, which makes it easier to attach them to table-top manipulators. (C) We designed and developed an attachable magnetic encoder to better detect the joint angle accuracy, removing the requirement for expensive motion capture gloves. (D) We equipped Ruka-v2 with e-flesh fingertips e-flesh body form factor for softer and compliant grip. This enables optional equipment of tactile sensors on the hand as well. Everything is open-source and accessible at our website: https://ruka-hand-v2.github.io/
• Figure 2: Ruka-v2 hardware overview. (A) Ruka-v2 features 18 degrees of freedom across the fingers and thumb, with joints at the DIP, PIP, MCP, and Adduction axes on each finger, and IP, MCP, and CMC joints on the thumb. An additional 2 DOF wrist provides flexion/extension and radial/ulnar deviation. (B) The independent knuckle module enables abduction/adduction at the MCP joints, allowing the fingers to splay and converge laterally. The middle finger remains fixed as a structural reference. (C) The 2 DOF wrist module supports near-human range of motion: flexion/extension (top) and radial/ulnar deviation (bottom), actuated independently via decoupled parallel linkages.
• Figure 3: 2 DOF wrist kinematics. (A) The wrist provides two independent degrees of freedom: flexion/extension (red arrow) and radial/ulnar deviation (blue arrow), both actuated through independent linkage chains meeting at a common pivot point. (B) The intersecting rotation axes share a single geometric center defined by a passive spherical ball joint. Each DOF is driven by a dedicated forearm motor via a rectangular linkage, decoupling the two axes and minimizing cross-axis coupling during wrist motion.
• Figure 4: Finger abduction/adduction mechanism. (Left) In the abducted state, the extension spring pulls the finger laterally outward, providing passive compliance and a well-defined neutral posture when the tendon is slack. (Right) Tendon-driven adduction: the adduction string is pulled by a forearm motor, rotating the knuckle module inward against the spring force. Blue arrows indicate the direction of applied force.
• Figure 5: DIP--PIP coupling mechanism. Fixed-length coupling strings (Red & Purple) routed through internal channels, enforce a deterministic relationship between PIP and DIP motion ($\alpha \approx \beta$).