Annotation-free 6-DoF Grasp Detection Method Integrating Physical and Geometric Priors

Authors

• Min Shi, School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
• Shisheng Guo, School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
• Suqin Wang, School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
• Zhaoxin Li, Agricultural Information Technology Research Laboratory, Chinese Academy of Agricultural Sciences, Beijing 100081, China; Key Laboratory of Agricultural Big Data, Ministry of Agriculture and Rural Affairs, Beijing 100081, China
• Dengming Zhu, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China; Taicang-CAS Institute of Information and Technology, Taicang 215400, China

Abstract

To improve the stability and cross-category generalization capability of grasp pose estimation in complex stacked scenes, an annotation-free 6-DoF grasp detection method integrating physical rules and geometric structure priors was proposed. In the offline stage, a template library of feasible grasp poses was constructed based on multi-physical constraints, without relying on manual grasp annotations. In the network design, the modeling of structural symmetry of objects and spatial overlap relationships was introduced; a geometric guidance mechanism with occlusion perception and exposure modeling capabilities was designed, and robust pose alignment of target objects was achieved by combining keypoint regression. A multi-type stacked dataset IP A-Stack ++was constructed, and tests were conducted in grasping tasks of single-category and mixed-category industrial parts.Experimental results show that the grasp success rate of the proposed method in single-type and multi-type scenes is significantly superior to other existing methods of the same type, demonstrating good grasp stability and versatility.

Recommended Citation

Shi, Min; Guo, Shisheng; Wang, Suqin; Li, Zhaoxin; and Zhu, Dengming (2026) "Annotation-free 6-DoF Grasp Detection Method Integrating Physical and Geometric Priors," Journal of System Simulation: Vol. 38: Iss. 5, Article 11.
DOI: 10.16182/j.issn1004731x.joss.25-0502
Available at: https://dc-china-simulation.researchcommons.org/journal/vol38/iss5/11

First Page

1290

Last Page

1302

CLC

TP391.9

Recommended Citation

Shi Min, Guo Shisheng, Wang Suqin, et al. Annotation-free 6-DoF Grasp Detection Method Integrating Physical and Geometric Priors[J]. Journal of System Simulation, 2026, 38(5): 1290-1302.

Corresponding Author

Wang Suqin

DOI

10.16182/j.issn1004731x.joss.25-0502