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ContactGrasp: Functional Multi-finger Grasp Synthesis from Contact
Open accessAbstract
Grasping and manipulating objects is an important human skill. Since most objects are designed to be manipulated by human hands, anthropomorphic hands can enable richer human-robot interaction. Desirable grasps are not only stable, but also functional: they enable post-grasp actions with the object. However, functional grasp synthesis for high degree-of-freedom anthropomorphic hands from object shape alone is challenging. We present ContactGrasp, a framework for functional grasp synthesis from object shape and contact on the object surface. Contact can be manually specified or obtained through demonstrations. Our contact representation is object-centric and allows functional grasp synthesis even for hand models different than the one used for demonstration. Using a dataset of contact demonstrations from humans grasping diverse household objects, we synthesize functional grasps for three hand models and two functional intents. The project webpage is https://contactdb.cc.gatech.edu/contactgrasp.html.
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“the contact forces that distinguish stable grasps from infeasible poses (Brahmbhatt et al., 2019) are unrecorded”
From Dexterous Robot Manipulation from Human Demonstrations via Contact-Anchored Retargeting and Residual Policy Learning (2026) · cites this paper as Brahmbhatt et al., 2019
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Citations
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Cited by
Sorted by citations
GraspNet-1Billion: A Large-Scale Benchmark for General Object Grasping
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Metadata
- Authors
- Brahmbhatt, S., Handa, A., Hays, J., & Fox, D.
- Affiliations
- Georgia Institute of Technology (US)
- Nvidia (United States) (US)
- Venue
- 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
- Publisher
- IEEE
- Published
- 2019-11
- Pages
- 2386-2393
- ISSN
- 2153-0858 (ISSN-L)
- OpenAlex
- W2934245910
- Cited by
- 125
- References
- 40
- Citations by year
- 2026: 6 · 2025: 19 · 2024: 34 · 2023: 26 · 2022: 22 · 2021: 11 · 2020: 6 · 2019: 1
- FWCI
- 15.46
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Robot Manipulation and Learning
- Physical Sciences › Engineering › Biomedical Engineering › Soft Robotics and Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Reinforcement Learning in Robotics
- Keywords
- anthropomorphic hand, object shape, human-robot interaction, household products, grasp stability
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