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Force-Aware 3D Contact Modeling for Stable Grasp Generation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

Contact-based grasp generation plays a crucial role in various applications. Recent methods typically focus on the geometric structure of objects, producing grasps with diverse hand poses and plausible contact points. However, these approaches often overlook the physical attributes of the grasp, specifically the contact force, leading to reduced stability of the grasp. In this paper, we focus on stable grasp generation using explicit contact force predictions. First, we define a force-aware contact representation by transforming the normal force value into discrete levels and encoding it using a one-hot vector. Next, we introduce force-aware stability constraints. We define the stability problem as an acceleration minimization task and explicitly relate stability with contact geometry by formulating the underlying physical constraints. Finally, we present a pose optimizer that systematically integrates our contact representation and stability constraints to enable stable grasp generation. We show that these constraints can help identify key contact points for stability which provide effective initialization and guidance for optimization towards a stable grasp. Experiments are carried out on two public benchmarks, showing that our method brings about 20% improvement in stability metrics and adapts well to novel objects. The source code will be released upon acceptance.
Original languageEnglish
Title of host publicationProceedings of the 40th AAAI Conference on Artificial Intelligence
Subtitle of host publicationAAAI-26 Technical Tracks 5
EditorsSven Koenig, Chad Jenkins, Matthew E. Taylor
PublisherAssociation for the Advancement of Artificial Intelligence
Pages3219-3227
Number of pages9
ISBN (Print)9781577359067
DOIs
Publication statusPublished - 17 Mar 2026
Event40th AAAI Conference on Artificial Intelligence - Singapore EXPO, Singapore, Singapore
Duration: 20 Jan 202627 Jan 2026
https://aaai.org/conference/aaai/aaai-26/

Publication series

NameProceedings of the AAAI Conference on Artificial Intelligence
Number5
Volume40
ISSN (Print)2159-5399
ISSN (Electronic)2374-3468

Conference

Conference40th AAAI Conference on Artificial Intelligence
Abbreviated titleAAAI-2026
Country/TerritorySingapore
CitySingapore
Period20/01/2627/01/26
Internet address

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