{"title":"在动态、未知、连续和混乱的环境中安全导航","authors":"Mike D'Arcy, Pooyan Fazli, D. Simon","doi":"10.1109/SSRR.2017.8088169","DOIUrl":null,"url":null,"abstract":"We introduce ProbLP, a probabilistic local planner, for safe navigation of an autonomous robot in dynamic, unknown, continuous, and cluttered environments. We combine the proposed reactive planner with an existing global planner and evaluate the hybrid in challenging simulated environments. The experiments show that our method achieves a 77% reduction in collisions over the straight-line local planner we use as a benchmark.","PeriodicalId":403881,"journal":{"name":"2017 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Safe navigation in dynamic, unknown, continuous, and cluttered environments\",\"authors\":\"Mike D'Arcy, Pooyan Fazli, D. Simon\",\"doi\":\"10.1109/SSRR.2017.8088169\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We introduce ProbLP, a probabilistic local planner, for safe navigation of an autonomous robot in dynamic, unknown, continuous, and cluttered environments. We combine the proposed reactive planner with an existing global planner and evaluate the hybrid in challenging simulated environments. The experiments show that our method achieves a 77% reduction in collisions over the straight-line local planner we use as a benchmark.\",\"PeriodicalId\":403881,\"journal\":{\"name\":\"2017 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR)\",\"volume\":\"58 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SSRR.2017.8088169\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSRR.2017.8088169","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Safe navigation in dynamic, unknown, continuous, and cluttered environments
We introduce ProbLP, a probabilistic local planner, for safe navigation of an autonomous robot in dynamic, unknown, continuous, and cluttered environments. We combine the proposed reactive planner with an existing global planner and evaluate the hybrid in challenging simulated environments. The experiments show that our method achieves a 77% reduction in collisions over the straight-line local planner we use as a benchmark.