Reconfigurable Holographic Surface Aided Collaborative Wireless SLAM Using Federated Learning for Autonomous Driving
文献类型：期刊论文
| 作者 | Zhang, Haobo2; Yang, Ziang2; Tian, Yonglin3 ; Zhang, Hongliang2; Di, Boya2; Song, Lingyang1,2
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| 刊名 | IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
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| 出版日期 | 2023-08-01 |
| 卷号 | 8期号:8页码:4031-4046 |
| ISSN号 | 2379-8858 |
| 关键词 | Autonomous driving federated learning metasurface reconfigurable holographic surface simultaneous localization and mapping |
| DOI | 10.1109/TIV.2023.3285592 |
| 通讯作者 | Song, Lingyang(lingyang.song@pku.edu.cn) |
| 英文摘要 | Simultaneous Localization and Mapping (SLAM) utilizing millimeter-wave (mmWave) radars is widely recognized as an essential component for autonomous driving applications. In this article, we present a Reconfigurable Holographic Surface (RHS)-aided SLAM system, incorporating federated learning. The hardware cost of autonomous driving systems can be significantly reduced by replacing the expensive phased array antennas, traditionally used in mmWave radars, with the low-cost RHS metasurface antenna. Furthermore, multiple vehicles can collaborate through the federated learning framework, obtaining additional sensed data to enhance SLAM performance. However, the distinctive radiation structure of the RHS and the information exchange within the federated learning framework introduce complexities to the overall SLAM system design. To address these challenges, we propose a multi-vehicle SLAM protocol that regulates RHS-based radar sensing and data processing across multiple vehicles. Additionally, we design algorithms for RHS radiation optimization and federated learning-based localization and mapping. Simulation results demonstrate the efficacy of the proposed approach when compared to existing phased array-based and non-cooperative schemes. |
| WOS关键词 | SIMULTANEOUS LOCALIZATION ; RADAR |
| 资助项目 | National Key R&D Program of China[2022YFE0111900] ; National Natural Science Foundation of China[62271012] ; National Natural Science Foundation of China[61941101] ; Beijing Natural Science Foundation[L212027] ; Beijing Natural Science Foundation[4222005] ; State Key Laboratory of Advanced Optical Communication Systems Networks, China ; Science and Technology Innovation Program of Hunan Provionce[2022RC4024] |
| WOS研究方向 | Computer Science ; Engineering ; Transportation |
| 语种 | 英语 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| WOS记录号 | WOS:001075333800006 |
| 资助机构 | National Key R&D Program of China ; National Natural Science Foundation of China ; Beijing Natural Science Foundation ; State Key Laboratory of Advanced Optical Communication Systems Networks, China ; Science and Technology Innovation Program of Hunan Provionce |
| 源URL | [http://ir.ia.ac.cn/handle/173211/53038]  |
| 专题 | 多模态人工智能系统全国重点实验室 |
| 通讯作者 | Song, Lingyang |
| 作者单位 | 1.Peking Univ, Sch Elect & Comp Engn, Shenzhen Grad Sch, Shenzhen 518055, Peoples R China 2.Peking Univ, Sch Elect, State Key Lab Adv Opt Commun Syst & Networks, Beijing 100871, Peoples R China 3.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Haobo,Yang, Ziang,Tian, Yonglin,et al. Reconfigurable Holographic Surface Aided Collaborative Wireless SLAM Using Federated Learning for Autonomous Driving[J]. IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,2023,8(8):4031-4046. |
| APA | Zhang, Haobo,Yang, Ziang,Tian, Yonglin,Zhang, Hongliang,Di, Boya,&Song, Lingyang.(2023).Reconfigurable Holographic Surface Aided Collaborative Wireless SLAM Using Federated Learning for Autonomous Driving.IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,8(8),4031-4046. |
| MLA | Zhang, Haobo,et al."Reconfigurable Holographic Surface Aided Collaborative Wireless SLAM Using Federated Learning for Autonomous Driving".IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 8.8(2023):4031-4046. |
入库方式： OAI收割
来源：自动化研究所
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