{"title":"基于遗传算法的拆弹机器人自主定位与映射","authors":"M. F. Hamza","doi":"10.1109/I2CACIS57635.2023.10193667","DOIUrl":null,"url":null,"abstract":"With the advancement of technology, the police and military personnel begin to rely on technology to perform tasks which in the past require manual intervention. Detecting bomb under the car has been one of the routines for police and military personnel during their mission to protect important individual from bomb threat. In this study, the localization, navigation and mapping of vehicle undercarriage are simulated. Navigation simulation includes the perimeter navigation, path planning and manual threat search. Perimeter navigation navigates the perimeter of the vehicle to construct a boundary condition for threat search. Path planning allows for automated threat search and three different methods were used to construct the path on random spot generated within the perimeter of the vehicle. The methods are heuristic (Greedy Method), GA, and GA optimized heuristic. Manual threat search allows user to define search area within the perimeter of the vehicle. Mapping of vehicle undercarriage is done by sweeping under the vehicle while scanning the undercarriage of the vehicle using distance sensor.","PeriodicalId":244595,"journal":{"name":"2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"GA Based Autonomous Self Localization and Mapping for Bomb Disposal Robot\",\"authors\":\"M. F. Hamza\",\"doi\":\"10.1109/I2CACIS57635.2023.10193667\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the advancement of technology, the police and military personnel begin to rely on technology to perform tasks which in the past require manual intervention. Detecting bomb under the car has been one of the routines for police and military personnel during their mission to protect important individual from bomb threat. In this study, the localization, navigation and mapping of vehicle undercarriage are simulated. Navigation simulation includes the perimeter navigation, path planning and manual threat search. Perimeter navigation navigates the perimeter of the vehicle to construct a boundary condition for threat search. Path planning allows for automated threat search and three different methods were used to construct the path on random spot generated within the perimeter of the vehicle. The methods are heuristic (Greedy Method), GA, and GA optimized heuristic. Manual threat search allows user to define search area within the perimeter of the vehicle. Mapping of vehicle undercarriage is done by sweeping under the vehicle while scanning the undercarriage of the vehicle using distance sensor.\",\"PeriodicalId\":244595,\"journal\":{\"name\":\"2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/I2CACIS57635.2023.10193667\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/I2CACIS57635.2023.10193667","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
GA Based Autonomous Self Localization and Mapping for Bomb Disposal Robot
With the advancement of technology, the police and military personnel begin to rely on technology to perform tasks which in the past require manual intervention. Detecting bomb under the car has been one of the routines for police and military personnel during their mission to protect important individual from bomb threat. In this study, the localization, navigation and mapping of vehicle undercarriage are simulated. Navigation simulation includes the perimeter navigation, path planning and manual threat search. Perimeter navigation navigates the perimeter of the vehicle to construct a boundary condition for threat search. Path planning allows for automated threat search and three different methods were used to construct the path on random spot generated within the perimeter of the vehicle. The methods are heuristic (Greedy Method), GA, and GA optimized heuristic. Manual threat search allows user to define search area within the perimeter of the vehicle. Mapping of vehicle undercarriage is done by sweeping under the vehicle while scanning the undercarriage of the vehicle using distance sensor.