https://github.com/kingchou007/Dexterous-Manipulation
A curated collection of resources, papers, and tools on dexterous manipulation.
https://github.com/kingchou007/Dexterous-Manipulation
List: Dexterous-Manipulation
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A curated collection of resources, papers, and tools on dexterous manipulation.
- Host: GitHub
- URL: https://github.com/kingchou007/Dexterous-Manipulation
- Owner: kingchou007
- Created: 2024-07-30T09:50:19.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2026-04-05T03:04:46.000Z (3 months ago)
- Last Synced: 2026-04-05T05:09:27.007Z (3 months ago)
- Topics: awesome-list, dexterous-manipulation, manipulation, robotics
- Homepage:
- Size: 18.6 KB
- Stars: 48
- Watchers: 3
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-humanoid-manipulation - Awesome-Dexterous-Manipulation - Resources on dexterous manipulation (Related Awesome Lists / robot_descriptions)
- ultimate-awesome - Dexterous-Manipulation - A curated collection of resources, papers, and tools on dexterous manipulation. (Other Lists / TeX Lists)
README
# Dexterous-Manipulation
Organize the paper about dexterous manipulation by my reading.
## Content
- [Dexterous-Manipulation](#dexterous-manipulation)
- [Content](#content)
- [Teleoperation](#teleoperation)
- [Reinforcement Learning](#reinforcement-learning)
- [Learning From Human](#learning-from-human)
- [Sim2Real](#sim2real)
- [Hardware System](#hardware-system)
- [Tactile Sensing](#tactile-sensing)
- [VLA](#vla)
- [Compliance and Force Control](#compliance-and-force-control)
- [Cool Idea](#cool-idea)
## Teleoperation
* (2025) Liu, Jason Jingzhou, et al. Factr: Force-attending curriculum training for contact-rich policy learning. - [arXiv](https://arxiv.org/abs/2502.17432)
* (2024) Wang, C., Shi, H., Wang, W., Zhang, R., Fei-Fei, L., & Liu, C. K. Dexcap: Scalable and portable mocap data collection system for dexterous manipulation. - [arXiv](https://arxiv.org/abs/2403.07788), [Website](https://dex-cap.github.io/)
* (2023) Qin, Y., Yang, W., Huang, B., Van Wyk, K., Su, H., Wang, X., ... & Fox, D. Anyteleop: A general vision-based dexterous robot arm-hand teleoperation system. - [arXiv](https://arxiv.org/abs/2307.04577), [Website](https://yzqin.github.io/anyteleop/)
* (2023) Arunachalam, S. P., Güzey, I., Chintala, S., & Pinto, L. Holo-dex: Teaching dexterity with immersive mixed reality. - [arXiv](https://arxiv.org/abs/2210.06463), [Website](https://holo-dex.github.io/)
* (2020) Handa, A., Van Wyk, K., Yang, W., Liang, J., Chao, Y. W., Wan, Q., ... & Fox, D. Dexpilot: Vision-based teleoperation of dexterous robotic hand-arm system. - [arXiv](https://arxiv.org/abs/1910.03135), [Website](https://sites.google.com/view/dex-pilot)
## Reinforcement Learning
* (2024) Ankile, L., Simeonov, A., Shenfeld, I., Torne, M., & Agrawal, P. From Imitation to Refinement--Residual RL for Precise Assembly. - [arXiv](https://arxiv.org/abs/2407.16677)
## Learning From Human
* (2025) Qiu, R. Z., Yang, S., Cheng, X., Chawla, C., Li, J., He, T., ... & Wang, X. Humanoid Policy~ Human Policy. - [arXiv](https://arxiv.org/abs/2503.13441), [Website](https://human-as-robot.github.io/)
* (2024) Kareer, S., Patel, D., Punamiya, R., Mathur, P., Cheng, S., Wang, C., ... & Xu, D. Egomimic: Scaling imitation learning via egocentric video. - [arXiv](https://arxiv.org/abs/2410.24221), [Website](https://egomimic.github.io/)
* (2022) Shaw, K., Bahl, S., & Pathak, D. Videodex: Learning dexterity from internet videos. - [arXiv](https://arxiv.org/abs/2212.04498), [Website](https://video-dex.github.io)
## Sim2Real
* (2025) Maddukuri, A., Jiang, Z., Chen, L. Y., Nasiriany, S., Xie, Y., Fang, Y., ... & Zhu, Y. Sim-and-Real Co-Training: A Simple Recipe for Vision-Based Robotic Manipulation. - [arXiv](https://co-training.github.io/resources/paper.pdf), [Website](https://co-training.github.io/)
* (2025) Lin, T., Sachdev, K., Fan, L., Malik, J., & Zhu, Y. Sim-to-Real Reinforcement Learning for Vision-Based Dexterous Manipulation on Humanoids. - [arXiv](https://arxiv.org/abs/2502.20396)
* (2023) Huang, B., Chen, Y., Wang, T., Qin, Y., Yang, Y., Atanasov, N., & Wang, X. Dynamic handover: Throw and catch with bimanual hands. - [arXiv](https://arxiv.org/pdf/2309.05655), [Website](https://binghao-huang.github.io/dynamic_handover/)
* (2023) Orbit: A Unified Simulation Framework for Interactive Robot Learning Environments. - [arXiv](https://arxiv.org/abs/2301.04195), [Website](https://isaac-orbit.github.io/)
* (2023) Chen, T., Tippur, M., Wu, S., Kumar, V., Adelson, E., & Agrawal, P. Visual dexterity: In-hand reorientation of novel and complex object shapes. - [arXiv](https://arxiv.org/abs/2211.11744)
## Hardware System
* (2024) Chi, C., Xu, Z., Pan, C., Cousineau, E., Burchfiel, B., Feng, S., Tedrake, R., & Song, S. Universal Manipulation Interface: In-The-Wild Robot Teaching Without In-The-Wild Robots. - [arXiv](https://arxiv.org/abs/2402.10329), [Website](https://umi-gripper.github.io)
* (2024) Romero, B., Fang, H. S., Agrawal, P., & Adelson, E. Eyesight hand: Design of a fully-actuated dexterous robot hand with integrated vision-based tactile sensors and compliant actuation. - [arXiv](https://arxiv.org/abs/2410.06440)
* (2023) Mannam, P., Shaw, K., Bauer, D., Oh, J., Pathak, D., & Pollard, N. Designing anthropomorphic soft hands through interaction. - [arXiv](https://arxiv.org/pdf/2306.04784)
* (2023) Shaw, K., Agarwal, A., & Pathak, D. Leap hand: Low-cost, efficient, and anthropomorphic hand for robot learning. - [arXiv](https://arxiv.org/abs/2309.06440)
* (2021) Kim, U., Jung, D., Jeong, H., Park, J., Jung, H. M., Cheong, J., ... & Park, C. Integrated linkage-driven dexterous anthropomorphic robotic hand. - [Paper](https://www.nature.com/articles/s41467-021-27261-0.pdf)
* (2012) Bridgwater, L. B., Ihrke, C. A., Diftler, M. A., Abdallah, M. E., Radford, N. A., Rogers, J. M., ... & Linn, D. M. The robonaut 2 hand-designed to do work with tools. - [Paper](https://ieeexplore.ieee.org/abstract/document/6224772/)
## Tactile Sensing
* (2025) Li, J., Wu, T., Zhang, J., Chen, Z., Jin, H., Wu, M., ... & Dong, H. Adaptive Visuo-Tactile Fusion with Predictive Force Attention for Dexterous Manipulation. - [arXiv](https://arxiv.org/abs/2505.13982), [Website](https://adaptac-dex.github.io/)
* (2025) Wu, Q., Wang, H., Zhou, J., Xiong, X., & Lou, Y. TARS: Tactile Affordance in Robot Synesthesia for Dexterous Manipulation. - [Paper](https://ieeexplore.ieee.org/abstract/document/10766612)
* (2024) Wu, T., Li, J., Zhang, J., Wu, M., & Dong, H. Canonical representation and force-based pretraining of 3d tactile for dexterous visuo-tactile policy learning. - [arXiv](https://arxiv.org/abs/2409.17549)
* (2021) Dong, S., Jha, D. K., Romeres, D., Kim, S., Nikovski, D., & Rodriguez, A. Tactile-rl for insertion: Generalization to objects of unknown geometry. - [arXiv](https://arxiv.org/pdf/2104.01167)
## VLA
* (2024) Kim, M. J., Pertsch, K., Karamcheti, S., Xiao, T., Balakrishna, A., Nair, S., ... & Finn, C. Openvla: An open-source vision-language-action model. - [arXiv](https://arxiv.org/abs/2406.09246), [Website](https://openvla.github.io/)
## Compliance and Force Control
* (2026) Shi, H., Hu, S., Hou, Y., Wang, W., Liu, K., & Song, S. Minimalist Compliance Control. - [arXiv](https://arxiv.org/abs/2603.00913), [Website](https://minimalist-compliance-control.github.io/)
* (2025) Margolis, G. B., Wang, M., Fey, N., & Agrawal, P. SoftMimic: Learning Compliant Whole-body Control from Examples. - [arXiv](https://arxiv.org/abs/2510.17792), [Website](https://gmargo11.github.io/softmimic/)
* (2025) Zhi, P., Li, P., Yin, J., Jia, B., & Huang, S. Learning a Unified Policy for Position and Force Control in Legged Loco-Manipulation. - [arXiv](https://arxiv.org/abs/2505.20829), [Website](https://unified-force.github.io/)
* (2024) Hou, Y., Liu, Z., Chi, C., Cousineau, E., Kuppuswamy, N., Feng, S., Burchfiel, B., & Song, S. Adaptive Compliance Policy: Learning Approximate Compliance for Diffusion Guided Control. - [arXiv](https://arxiv.org/abs/2410.09309), [Website](https://adaptive-compliance.github.io/)
## Cool Idea
* (2023) Zakka, K., Wu, P., Smith, L., Gileadi, N., Howell, T., Peng, X. B., ... & Abbeel, P. Robopianist: Dexterous piano playing with deep reinforcement learning. - [arXiv](https://arxiv.org/abs/2304.04150), [Code](https://kzakka.com/robopianist/), [Website](https://github.com/google-research/robopianist)