MuJoCo HAPTIX: A virtual reality system for hand manipulation
Abstract
Data-driven methods have lead to advances in multiple fields including robotics. These methods however have had limited impact on dexterous hand manipulation, partly due to lack of rich and physically-consistent dataset as well as technology able to collect them. To fill this gap, we developed a virtual reality system combining real-time motion capture, physics simulation and stereoscopic visualization. The system enables a user wearing a CyberGlove to "reach-in" the simulation, and manipulate virtual objects through contacts with a tele-operated virtual hand. The system is evaluated on a subset of tasks in the Southampton Hand Assessment Procedure - which is a clinically validated test of hand function. The system is also being used by performer teams in the DARPA Hand Proprioception & Touch Interfaces program to develop neural control interfaces in simulation. The software is freely available at www.mujoco.org.
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Different three-dimensional object shapes have inherent different complexities.
“We integrated three basic types of three-dimensional object shapes to not only introduce the inherent different complexities that come with such objects, but also allowing us to assess different grasping techniques [47], [48].”
From Study of Multimodal Interfaces and the Improvements on Teleoperation (2020) · cites this paper as [48]
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Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations
Rajeswaran, A., Kumar, V., Gupta, A., Vezzani, G., Schulman, J., Todorov, E., & Levine, S. (2018) · Robotics: Science and Systems XIV · doi:10.15607/rss.2018.xiv.049 · Cited by 847 · see citing works
Self-citationDeep Imitation Learning for Complex Manipulation Tasks from Virtual Reality Teleoperation
Zhang, T., McCarthy, Z., Jow, O., Lee, D., Chen, X., Goldberg, K., & Abbeel, P. (2018) · 2018 IEEE International Conference on Robotics and Automation (ICRA) · doi:10.1109/icra.2018.8461249 · Cited by 609 · see citing works
Study of Multimodal Interfaces and the Improvements on Teleoperation
Triantafyllidis, E., Mcgreavy, C., Gu, J., & Li, Z. (2020) · IEEE Access · doi:10.1109/access.2020.2990080 · Cited by 105 · see citing works
“We integrated three basic types of three-dimensional object shapes to not only introduce the inherent different complexities that come with such objects, but also allowing us to assess different grasping techniques [47], [48].”
BackgroundA bioelectric neural interface towards intuitive prosthetic control for amputees
Nguyen, A. T., Xu, J., Jiang, M., Luu, D. K., Wu, T., Tam, W.-K., Zhao, W., Drealan, M. W., Overstreet, C. K., Zhao, Q., et al. (2020) · Journal of Neural Engineering · doi:10.1088/1741-2552/abc3d3 · Cited by 52 · see citing works
- Authors
- Kumar, V., & Todorov, E.
- Affiliations
- University of Washington (US)
- ORCID
- Kumar, Vikash
- Venue
- 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids)
- Publisher
- IEEE
- Published
- 2015-11
- Pages
- 657-663
- OpenAlex
- W2213758982
- Cited by
- 102
- References
- 0
- Citations by year
- 2026: 5 · 2025: 11 · 2024: 16 · 2023: 14 · 2022: 9 · 2021: 14 · 2020: 9 · 2019: 10 · 2018: 8 · 2017: 2 · 2016: 4
- FWCI
- 12.57
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE-RAS International Conference on Humanoid Robots (Humanoids) (publishedVersion)
- Funders
- Defense Advanced Research Projects Agency
- Topics
- Physical Sciences › Engineering › Mechanical Engineering › Teleoperation and Haptic Systems
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Physical Sciences › Computer Science › Human-Computer Interaction › Interactive and Immersive Displays
- Keywords
- virtual reality, teleoperation, real-time motion capture, physics simulation, stereoscopic visualization, CyberGlove, Southampton Hand Assessment Procedure, hand function assessment, touch interfaces, MuJoCo
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