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HTTP/1.1 302 FOUND Server: nginx/1.18.0 (Ubuntu) Date: Mon, 29 Dec 2025 00:40:01 GMT Content-Type: text/html; charset=utf-8 Content-Length: 233 Connection: keep-alive Location: https://v1.leaphand.com HTTP/2 200 server: GitHub.com content-type: text/html; charset=utf-8 last-modified: Tue, 26 Aug 2025 19:18:07 GMT access-control-allow-origin: * etag: W/"68ae086f-c64d" expires: Mon, 29 Dec 2025 00:50:01 GMT cache-control: max-age=600 content-encoding: gzip x-proxy-cache: MISS x-github-request-id: 6995:3FD64F:81C327:91C6CB:6951CDE0 accept-ranges: bytes age: 0 date: Mon, 29 Dec 2025 00:40:01 GMT via: 1.1 varnish x-served-by: cache-bom-vanm7210090-BOM x-cache: MISS x-cache-hits: 0 x-timer: S1766968802.629248,VS0,VE210 vary: Accept-Encoding x-fastly-request-id: 4307c4dc08ada2eaba96503b8b5a674a9c202808 content-length: 7436 LEAP Hand: Low-Cost, Efficient, and Anthropomorphic Hand for Robot Learning

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LEAP Hand:

Low-Cost, Efficient, and Anthropomorphic Hand for Robot Learning

Kenneth Shaw Ananye Agrawal Deepak Pathak
Carnegie Mellon University
RSS 2023

RSS 2023 arXiv Poster Video Summary API Isaac Gym Isaac Lab Gloves Vision Pro

RSS 2025 News: We are demoing LEAP Hand at RSS on Tuesday 6/24. For our tendon-driven hands, visit
v2-adv.leaphand.com for our new fully-released advanced robot hand and a preview of v2.leaphand.com for a simple low-cost version ($200-$300).

Abstract

Dexterous manipulation has been a long-standing challenge in robotics. While machine learning techniques have shown some promise, results have largely been currently limited to simulation. This can be mostly attributed to the lack of suitable hardware. In this paper, we present LEAP Hand, a low-cost dexterous and anthropomorphic hand for machine learning research. In contrast to previous hands, LEAP Hand has a novel kinematic structure that allows maximal dexterity regardless of finger pose. LEAP Hand is low-cost and can be assembled in 4 hours at a cost of 2000 USD from readily available parts. It is capable of consistently exerting large torques over long durations of time. We show that LEAP Hand can be used to perform several manipulation tasks in the real world—from visual teleoperation to learning from passive video data and sim2real. LEAP Hand significantly outperforms its closest competitor Allegro Hand in all our experiments while being 1/8th of the cost. We release the URDF model, 3D CAD files, tuned simulation environment, and a development platform with useful APIs on our website at https://leaphand.com

Thanks to your incredible support this past year, LEAP Hand has become the leading robotic hand platform for machine learning research! We remain committed to actively supporting and developing LEAP Hand.

Accurate Teleoperation With Gloves:

We demo every year at CoRL and RSS!

Tweet Code

Our live demo at RSS 2023, thanks Aleksei Petrenko for the video!

Autonomous Results using Gloves for data collection.

Teleoperation from Uncalibrated Human Video

Behavior Cloning with Internet Videos

Kinematics and Dexterity:

LEAP hand demonstrates side to side dexterity in both the finger up and finger down configuration.
This is thanks to its universal abduction-adduction mechanism.

Cost

LEAP Hand costs under $2000 and can be assembled in under three hours using only common hand tools.

Strength

LEAP Hand is one of the strongest robotic hands available today

Robustness

LEAP Hand can accurately complete repeated motions without overheating

Human-like Versatility

LEAP Hand can grasp a wide variety of objects easily

BibTeX

@article{shaw2023leaphand,
      title={LEAP Hand: Low-Cost, Efficient, and Anthropomorphic Hand for Robot Learning},
      author={Shaw, Kenneth and Agarwal, Ananye and Pathak, Deepak},
      journal={Robotics: Science and Systems (RSS)},
      year={2023}}

Acknowledgements

We thank Shikhar Bahl, Russell Mendonca, Unnat Jain and Jianren Wang for fruitful discussions about the project. KS is supported by NSF Graduate Research Fellowship under Grant No. DGE2140739. This work is supported by ONR N00014-22-1-2096 and the DARPA Machine Common Sense grant.

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