{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T14:48:52Z","timestamp":1764859732514,"version":"3.46.0"},"reference-count":34,"publisher":"Association for Computing Machinery (ACM)","issue":"4","funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62220106011"],"award-info":[{"award-number":["62220106011"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Southeast University Interdisciplinary Research Program for Young Scholars","award":["2024FGC1006"],"award-info":[{"award-number":["2024FGC1006"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Reconfigurable Technol. Syst."],"published-print":{"date-parts":[[2025,12,31]]},"abstract":"<jats:p>\n                    Point cloud registration is a fundamental task in LiDAR-based localization and mapping, widely employed in robotics and autonomous vehicles. However, existing registration solutions lose geometric topology continuity and lack scanline-aware, configurable correspondence search, restricting their real-time applicability. To solve these issues, we propose a fundamentally re-architected, energy-efficient FPGA framework for real-time point cloud registration, featuring a configurable, multi-mode correspondence search engine. First, we introduce a scanline-aided range-projection structure (SA-RPS) that reorganizes LiDAR points within configurable segmentation domains into contiguous memory while preserving scanline topology, enabling efficient and flexible multi-mode correspondence search. Second, we develop a deeply pipelined, ultra-fast SA-RPS-based correspondence search (SA-RPS-CS) accelerator that supports dynamic configuration of search mode and parallelism and incorporates a sliding-window cache and scanline-aware K-selection module for high-throughput, multi-mode correspondence extraction. Third, we present a co-designed registration framework that integrates the accelerator with dynamic parameter configuration, enabling adaptive, real-time processing across diverse SLAM scenarios. Experimental results demonstrate that the proposed SA-RPS-CS accelerator delivers\n                    <jats:inline-formula content-type=\"math\/tex\">\n                      <jats:tex-math notation=\"LaTeX\" version=\"MathJax\">\\(2.3\\times\\)<\/jats:tex-math>\n                    <\/jats:inline-formula>\n                    \u2009\u2013\u2009\n                    <jats:inline-formula content-type=\"math\/tex\">\n                      <jats:tex-math notation=\"LaTeX\" version=\"MathJax\">\\(32.4\\times\\)<\/jats:tex-math>\n                    <\/jats:inline-formula>\n                    faster search and\n                    <jats:inline-formula content-type=\"math\/tex\">\n                      <jats:tex-math notation=\"LaTeX\" version=\"MathJax\">\\(1.8\\times\\)<\/jats:tex-math>\n                    <\/jats:inline-formula>\n                    \u2009\u2013\u2009\n                    <jats:inline-formula content-type=\"math\/tex\">\n                      <jats:tex-math notation=\"LaTeX\" version=\"MathJax\">\\(26.2\\times\\)<\/jats:tex-math>\n                    <\/jats:inline-formula>\n                    higher energy efficiency than previous state-of-the-art FPGA designs, achieving real-time registration for 64-channel LiDAR at 21.5 FPS with negligible loss in accuracy.\n                  <\/jats:p>","DOI":"10.1145\/3771768","type":"journal-article","created":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T15:44:49Z","timestamp":1760543089000},"page":"1-30","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["An Energy-Efficient and Real-Time FPGA-Based Point Cloud Registration Framework with Ultra-Fast and Configurable Multi-Mode Correspondence Search"],"prefix":"10.1145","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5150-487X","authenticated-orcid":false,"given":"Qi","family":"Deng","sequence":"first","affiliation":[{"name":"School of Micro-electronics, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China, School of Information Science and Technology, ShanghaiTech University, Shanghai, China and School of Electronic Electrical and Communication Engineering, University of the Chinese Academy of Sciences, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4518-2533","authenticated-orcid":false,"given":"Hao","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Electronic Science and Engineering, Southeast University, Nanjing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0357-4507","authenticated-orcid":false,"given":"Yuhao","family":"Shu","sequence":"additional","affiliation":[{"name":"College of Integrated Circuits, Nanjing University of Aeronautics and Astronautics, Nanjing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-0677-0399","authenticated-orcid":false,"given":"Jianzhong","family":"Xiao","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6014-6453","authenticated-orcid":false,"given":"Weixiong","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-6994-2618","authenticated-orcid":false,"given":"Hui","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Micro-electronics, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4244-5916","authenticated-orcid":false,"given":"Yajun","family":"Ha","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China and Shanghai Engineering Research Center of Energy Efficient and Custom AI IC, Shanghai, China"}]}],"member":"320","published-online":{"date-parts":[[2025,12,4]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/TVLSI.2022.3147743"},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1145\/3613424.3614290"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/HPCA56546.2023.10070940"},{"key":"e_1_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2022.3142188"},{"key":"e_1_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSII.2021.3095764"},{"key":"e_1_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/IROS40897.2019.8967693"},{"key":"e_1_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1109\/MICRO61859.2024.00116"},{"key":"e_1_3_1_9_2","first-page":"442","volume-title":"4th International Conference on 3D Digital Imaging and Modeling 2003 (3DIM \u201903)","author":"Greenspan Michael","year":"2003","unstructured":"Michael Greenspan and Mike Yurick. 2003. 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