E. Ahmed, Hossam E. Abd El Munim, Hassan M. Shehata Bedour
{"title":"一种加速路径规划方法","authors":"E. Ahmed, Hossam E. Abd El Munim, Hassan M. Shehata Bedour","doi":"10.1109/ICCES.2018.8639491","DOIUrl":null,"url":null,"abstract":"Path planning is critical in robotics as well as autonomous driving applications. This research provides a modified path planning algorithm by enhancing the performance of the probabilistic roadmap (PRM) approach. The proposed technique is based on dividing the domain of motion and solves the relative path in each division. Our results on synthetic maps show a dramatic reduction on processing time compared with the conventional algorithm.","PeriodicalId":113848,"journal":{"name":"2018 13th International Conference on Computer Engineering and Systems (ICCES)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Accelerated Path Planning Approach\",\"authors\":\"E. Ahmed, Hossam E. Abd El Munim, Hassan M. Shehata Bedour\",\"doi\":\"10.1109/ICCES.2018.8639491\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Path planning is critical in robotics as well as autonomous driving applications. This research provides a modified path planning algorithm by enhancing the performance of the probabilistic roadmap (PRM) approach. The proposed technique is based on dividing the domain of motion and solves the relative path in each division. Our results on synthetic maps show a dramatic reduction on processing time compared with the conventional algorithm.\",\"PeriodicalId\":113848,\"journal\":{\"name\":\"2018 13th International Conference on Computer Engineering and Systems (ICCES)\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 13th International Conference on Computer Engineering and Systems (ICCES)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCES.2018.8639491\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 13th International Conference on Computer Engineering and Systems (ICCES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCES.2018.8639491","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Path planning is critical in robotics as well as autonomous driving applications. This research provides a modified path planning algorithm by enhancing the performance of the probabilistic roadmap (PRM) approach. The proposed technique is based on dividing the domain of motion and solves the relative path in each division. Our results on synthetic maps show a dramatic reduction on processing time compared with the conventional algorithm.