Self-adaptive metasurface platform based on computer vision

被引:21
|
作者
Yu, Qian [1 ]
Zheng, Yi Ning [1 ]
Gu, Ze [1 ]
Liu, Jia [1 ]
Liang, Yu Chen [1 ]
Li, Lin Zhou [1 ]
Zhang, Xin Ge [1 ]
Jiang, Wei Xiang [1 ]
机构
[1] Southeast Univ, Sch Informat Sci & Engn, State Key Lab Millimeter Waves, Nanjing 210096, Peoples R China
基金
中国国家自然科学基金;
关键词
CLOAK;
D O I
10.1364/OL.427527
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Programmable metasurfaces allow real-time electromagnetic (EM) manipulation in a digital manner, showing great potential to construct advanced multifunctional EM devices. However, the current programmable metasurfaces typically need human participation to achieve various EM functions. In this Letter, we propose, design, and construct a self-adaptive metasurface platform that can achieve beam control automatically based on image recognition. Such a platform is composed of a metasurface with 36 x 36 active units, a single-board computer, and two independent cameras that can detect the position of the objects. The single-board computer, Raspberry Pi, is used to calculate the information of the objects and generate the coding sequences to control the digital metasurface based on a low complexity binocular localization algorithm. Such a smart metasurface platform can generate different beams according to the location of the receiver and can be used as intelligent antennas in future communications and radars. (C) 2021 Optical Society of America
引用
收藏
页码:3520 / 3523
页数:4
相关论文
共 50 条
  • [21] Vision-Based Self-Adaptive Gripping in a Trimodal Robotic Sorting End-Effector
    Sadeghian, Rasoul
    Shahin, Shahrooz
    Sareh, Sina
    IEEE ROBOTICS AND AUTOMATION LETTERS, 2022, 7 (02) : 2124 - 2131
  • [22] Towards a distributed Continuum Computing platform for Federated Learning Based Self-Adaptive IoT Applications
    Abdennadher, Nabil
    2024 13TH MEDITERRANEAN CONFERENCE ON EMBEDDED COMPUTING, MECO 2024, 2024, : 2 - 2
  • [23] Self-Adaptive Architecture for Multi-Sensor Embedded Vision System
    Isavudeen, Ali
    Dokladalova, Eva
    Ngan, Nicolas
    Akil, Mohamed
    MATHEMATICAL AND ENGINEERING METHODS IN COMPUTER SCIENCE, MEMICS 2015, 2016, 9548 : 67 - 78
  • [24] Self-Adaptive Integrator for Multi-B2B Platform
    Wasilewski, Adam
    Steplowski, Jakub
    VISION 2025: EDUCATION EXCELLENCE AND MANAGEMENT OF INNOVATIONS THROUGH SUSTAINABLE ECONOMIC COMPETITIVE ADVANTAGE, 2019, : 13361 - 13368
  • [25] A Platform to Enable Self-Adaptive Cloud Applications Using Trustworthiness Properties
    D'Abruzzo Pereira, Jose
    Silva, Rui
    Antunes, Nuno
    Silva, Jorge L. M.
    de Franca, Breno
    Moraes, Regina
    2020 IEEE/ACM 15TH INTERNATIONAL SYMPOSIUM ON SOFTWARE ENGINEERING FOR ADAPTIVE AND SELF-MANAGING SYSTEMS, SEAMS, 2020, : 71 - 77
  • [26] Self-adaptive learning based immune algorithm
    Bin Xu
    Yi Zhuang
    Yu Xue
    Zhou Wang
    Journal of Central South University, 2012, 19 : 1021 - 1031
  • [27] Self-adaptive learning based immune algorithm
    Xu Bin
    Zhuang Yi
    Xue Yu
    Wang Zhou
    JOURNAL OF CENTRAL SOUTH UNIVERSITY, 2012, 19 (04) : 1021 - 1031
  • [28] Self-Adaptive System Verification based on SysML
    Lee, Seung-Min
    Park, Soojin
    Park, Young B.
    2019 INTERNATIONAL CONFERENCE ON ELECTRONICS, INFORMATION, AND COMMUNICATION (ICEIC), 2019, : 306 - 308
  • [29] A Monitor Method based on Adaptive Frequency for Self-Adaptive Software
    Cheng, Wen
    Li, Qingshan
    Wang, Lu
    PROCEEDINGS OF 2019 IEEE 10TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND SERVICE SCIENCE (ICSESS 2019), 2019, : 149 - 152
  • [30] Self-adaptive learning based immune algorithm
    许斌
    庄毅
    薛羽
    王洲
    Journal of Central South University, 2012, 19 (04) : 1021 - 1031