AcousNet: A Deep Learning Based Approach to Dynamic 3D Holographic Acoustic Field Generation From Phased Transducer Array

doi:10.1109/LRA.2021.3130368

	AcousNet: A Deep Learning Based Approach to Dynamic 3D Holographic Acoustic Field Generation From Phased Transducer Array
	Chengxi Zhong1 ; Yuyu Jia1 ; David C. Jeong 2; Yao Guo 3; Song Liu4,5
	2022-04-01
发表期刊	IEEE ROBOTICS AND AUTOMATION LETTERS (IF:4.6[JCR-2023],5.5[5-Year])
ISSN	2377-3774
卷号	7 期号:2 页码:666-673
发表状态	已发表
DOI	10.1109/LRA.2021.3130368
摘要	Holographic acoustic field has shown great potential for non-contact robotic manipulations of millimeter or sub-millimeter size objects to effectively deliver acoustic power. The latest technology for generating dynamic holographic acoustic field is through phased transducer array, where relative phases of emitted acoustic waves from transducers are independently controlled to modulate the acoustic interference field. While the forward kinematics of a phased array based robotic manipulation system is simple and straightforward, the inverse kinematics (i.e., the mapping from a given holographic acoustic field to array phases for control purpose), however, is mathematically non-linear and unsolvable, presenting challenges in developing wider applications of holographic acoustic field for robotic manipulation. Considering, thus far, there are still no effective solutions reported, the authors put intensive efforts to solve this problem using a machine learning approach, namely a deep neural network architecture, which we refer to as AcousNet. Experimental results demonstrate the effectiveness of the proposed method for dynamic holographic acoustic field generation from phased transducer array.
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收录类别	SCI ; SCIE ; EI
来源库	IEEE
引用统计	正在获取...
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/133092
专题	信息科学与技术学院信息科学与技术学院_博士生信息科学与技术学院_PI研究组_刘松组
作者单位	1.ShanghaiTech Automation and Robotics Center, ShanghaiTech University, Shanghai, China 2.Department of Communication, Santa Clara University, Santa Clara, CA, USA 3.Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China 4.School of Information Science and Technology, ShanghaiTech University, Shanghai, China 5.Shanghai Engineering Research Center of Intelligent Vision and Imaging, Shanghai, China
第一作者单位	上海科技大学
第一作者的第一单位	上海科技大学
推荐引用方式 GB/T 7714	Chengxi Zhong,Yuyu Jia,David C. Jeong,et al. AcousNet: A Deep Learning Based Approach to Dynamic 3D Holographic Acoustic Field Generation From Phased Transducer Array[J]. IEEE ROBOTICS AND AUTOMATION LETTERS,2022,7(2):666-673.
APA	Chengxi Zhong,Yuyu Jia,David C. Jeong,Yao Guo,&Song Liu.(2022).AcousNet: A Deep Learning Based Approach to Dynamic 3D Holographic Acoustic Field Generation From Phased Transducer Array.IEEE ROBOTICS AND AUTOMATION LETTERS,7(2),666-673.
MLA	Chengxi Zhong,et al."AcousNet: A Deep Learning Based Approach to Dynamic 3D Holographic Acoustic Field Generation From Phased Transducer Array".IEEE ROBOTICS AND AUTOMATION LETTERS 7.2(2022):666-673.