{"title":"A Lane Detection Hardware Algorithm Based on Helmholtz Principle and Its Application to Unmanned Mobile Vehicles","authors":"Katsuaki Kamimae, Shintaro Matsui, Yasutoshi Araki, Takehiro Miura, Keigo Motoyoshi, Keizo Yamashita, Haruto Ikehara, Takuho Kawazu, Huang Yuwei, Masahiro Nishimura, Shuto Abe, Kenyu Okino, Yuta Hashiguchi, Koki Fukuda, Kengo Yanagihara, Taito Manabe, Yuichiro Shibata","doi":"10.1109/ICFPT56656.2022.9974208","DOIUrl":null,"url":null,"abstract":"We are developing an SoC FPGA-based unmanned mobile vehicle for the FPGA design competition. For the vehicle to follow roads successfully, it must be able to detect not only straight lines but also curved lines accurately. Therefore, we implemented a lane detection algorithm that is robust not only against straight lines but also against curves to improve driving performance. We implemented an autonomous driving system employing this algorithm on Digilent Zybo Z7-20. We evaluated the lane detection algorithm based on simulations and showed that this algorithm can reduce false detection of lane features compared to the classical Canny filter.","PeriodicalId":239314,"journal":{"name":"2022 International Conference on Field-Programmable Technology (ICFPT)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Field-Programmable Technology (ICFPT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICFPT56656.2022.9974208","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
We are developing an SoC FPGA-based unmanned mobile vehicle for the FPGA design competition. For the vehicle to follow roads successfully, it must be able to detect not only straight lines but also curved lines accurately. Therefore, we implemented a lane detection algorithm that is robust not only against straight lines but also against curves to improve driving performance. We implemented an autonomous driving system employing this algorithm on Digilent Zybo Z7-20. We evaluated the lane detection algorithm based on simulations and showed that this algorithm can reduce false detection of lane features compared to the classical Canny filter.
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