Ryota Miyagi, N. Takagi, Sho Kinoshista, M. Oda, Hideki Takase
{"title":"Zytlebot : FPGA integrated ros-based autonomous mobile robot","authors":"Ryota Miyagi, N. Takagi, Sho Kinoshista, M. Oda, Hideki Takase","doi":"10.1109/ICFPT52863.2021.9609883","DOIUrl":null,"url":null,"abstract":"The FPT 2021 Design Competition aims to improve the technology of utilizing FPGA and achieve level-5 autonomous driving. We developed FPGA Integrated ROS-Based autonomous mobile robot, ZytleBot, for the competition. ZytleBot collects environmental information with CMOS cameras, recognizes environments, decides its action on programmable SoC, and controls its actuator. As a result, ZytleBot can run road model courses, detect and adequately deal with traffic lights and obstacles. We used the robot development platform TurtleBot3 and the robot middleware ROS to develop the robot system quickly. In addition, we utilize FPGA to accelerate road-images processing and traffic lights recognition using the HOG feature and SVM classifier. As a result, traffic lights recognition with FPGA is 270 times faster than those only with CPU.","PeriodicalId":376220,"journal":{"name":"2021 International Conference on Field-Programmable Technology (ICFPT)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Field-Programmable Technology (ICFPT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICFPT52863.2021.9609883","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The FPT 2021 Design Competition aims to improve the technology of utilizing FPGA and achieve level-5 autonomous driving. We developed FPGA Integrated ROS-Based autonomous mobile robot, ZytleBot, for the competition. ZytleBot collects environmental information with CMOS cameras, recognizes environments, decides its action on programmable SoC, and controls its actuator. As a result, ZytleBot can run road model courses, detect and adequately deal with traffic lights and obstacles. We used the robot development platform TurtleBot3 and the robot middleware ROS to develop the robot system quickly. In addition, we utilize FPGA to accelerate road-images processing and traffic lights recognition using the HOG feature and SVM classifier. As a result, traffic lights recognition with FPGA is 270 times faster than those only with CPU.