Learning-Based Slip Detection for Dexterous Manipulation Using GelStereo Sensing

doi:10.1109/TNNLS.2023.3270579

	Learning-Based Slip Detection for Dexterous Manipulation Using GelStereo Sensing
	Cui, Shaowei1 ; Wang, Shuo1,2,3 ; Wang, Rui1 ; Zhang, Shaolin1 ; Zhang, Chaofan 2,4
发表期刊	IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
ISSN	2162-237X
	2023-05-24
页码	10
通讯作者	Wang, Shuo(shuo.wang@ia.ac.cn)
摘要	Endowing the robot with tactile perception can effectively improve manipulation dexterity, along with various benefits of human-like touch. Using GelStereo (GS) tactile sensing, which gives high-resolution contact geometry information, including 2-D displacement field, and 3-D point cloud of the contact surface, we present a learning-based slip detection system in this study. The results reveal that the well-trained network achieves 95.79% accuracy on the never-seen testing dataset, which surpasses the current model-based and learning-based methods using visuotactile sensing. We also propose a general framework for slip feedback adaptive control for dexterous robot manipulation tasks. The experimental results show the effectiveness and efficiency of the proposed control framework using GS tactile feedback when deployed on real-world grasping and screwing manipulation tasks on various robot setups.
关键词	Sensors Task analysis Three-dimensional displays Point cloud compression Feature extraction Adaptive control Grasping Dexterous manipulation slip detection slip feedback control tactile sensing
DOI	10.1109/TNNLS.2023.3270579
关键词[WOS]	TACTILE ; LOCALIZATION
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2018AAA0103003] ; National Natural Science Foundation of China[62273342] ; National Natural Science Foundation of China[62122087] ; Beijing Natural Science Foundation[4222055] ; CIE-Tencent Robotics X Rhino-Bird Focused Research Program
项目资助者	National Key Research and Development Program of China ; National Natural Science Foundation of China ; Beijing Natural Science Foundation ; CIE-Tencent Robotics X Rhino-Bird Focused Research Program
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号	WOS:001005817500001
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/53463
专题	多模态人工智能系统全国重点实验室
通讯作者	Wang, Shuo
作者单位	1.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai 200031, Peoples R China 4.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Cui, Shaowei,Wang, Shuo,Wang, Rui,et al. Learning-Based Slip Detection for Dexterous Manipulation Using GelStereo Sensing[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2023:10.
APA	Cui, Shaowei,Wang, Shuo,Wang, Rui,Zhang, Shaolin,&Zhang, Chaofan.(2023).Learning-Based Slip Detection for Dexterous Manipulation Using GelStereo Sensing.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,10.
MLA	Cui, Shaowei,et al."Learning-Based Slip Detection for Dexterous Manipulation Using GelStereo Sensing".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2023):10.