{"title":"基于飞蛾羽流追踪策略的源识别算法优化","authors":"Wei Li, Joseph E. Sutton","doi":"10.1109/CIRA.2007.382842","DOIUrl":null,"url":null,"abstract":"This paper presents a method of designing and optimizing a single chemical sensor-based source identification algorithm, derived from moth-inspired chemical plume tracing (CPT) strategies. In doing it, we define a source identification zone (SIZ) using last chemical detection points (LCDPs). Then, we optimize the proposed algorithm using a simulated plume with significant meander and filament intermittency by considering dynamics of a REMUS vehicle. The simulation studies show that for 1000 test runs the optimized algorithm achieves a success rate of over 90% in identifying source locations, an average identification time of 3-4 minutes, and an average error of identified source locations 1~2 meters in an operation area with length scales of 100 meters. In addition, we discuss an extension of the moth-inspired strategies to trace a plume and identify the odor source with static location in a three-dimensional space.","PeriodicalId":301626,"journal":{"name":"2007 International Symposium on Computational Intelligence in Robotics and Automation","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Optimization of Source Identification Algorithm Derived from Moth-Inspired Plume Tracing Strategies\",\"authors\":\"Wei Li, Joseph E. Sutton\",\"doi\":\"10.1109/CIRA.2007.382842\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a method of designing and optimizing a single chemical sensor-based source identification algorithm, derived from moth-inspired chemical plume tracing (CPT) strategies. In doing it, we define a source identification zone (SIZ) using last chemical detection points (LCDPs). Then, we optimize the proposed algorithm using a simulated plume with significant meander and filament intermittency by considering dynamics of a REMUS vehicle. The simulation studies show that for 1000 test runs the optimized algorithm achieves a success rate of over 90% in identifying source locations, an average identification time of 3-4 minutes, and an average error of identified source locations 1~2 meters in an operation area with length scales of 100 meters. In addition, we discuss an extension of the moth-inspired strategies to trace a plume and identify the odor source with static location in a three-dimensional space.\",\"PeriodicalId\":301626,\"journal\":{\"name\":\"2007 International Symposium on Computational Intelligence in Robotics and Automation\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 International Symposium on Computational Intelligence in Robotics and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIRA.2007.382842\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Symposium on Computational Intelligence in Robotics and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIRA.2007.382842","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimization of Source Identification Algorithm Derived from Moth-Inspired Plume Tracing Strategies
This paper presents a method of designing and optimizing a single chemical sensor-based source identification algorithm, derived from moth-inspired chemical plume tracing (CPT) strategies. In doing it, we define a source identification zone (SIZ) using last chemical detection points (LCDPs). Then, we optimize the proposed algorithm using a simulated plume with significant meander and filament intermittency by considering dynamics of a REMUS vehicle. The simulation studies show that for 1000 test runs the optimized algorithm achieves a success rate of over 90% in identifying source locations, an average identification time of 3-4 minutes, and an average error of identified source locations 1~2 meters in an operation area with length scales of 100 meters. In addition, we discuss an extension of the moth-inspired strategies to trace a plume and identify the odor source with static location in a three-dimensional space.