{"title":"多目标导航救援机器人的退火制导","authors":"C. Luo, S. Furao, Simon X. Yang, Hongwei Mo","doi":"10.1109/ICINFA.2015.7279406","DOIUrl":null,"url":null,"abstract":"Mission of a rescue robot is to search for some certain points and find trapped people or valuables to be rescued in an unknown terrain. A rescue robot should be able to be navigated to multiple goals. In this paper, a multi-goal navigation and mapping solution is found by simulated annealing (SA) based multi-goal navigation integrated a local navigator. The robot is guided by SA-based multi-goal route planner to search for multiple goals. Among goals, the robot is navigated by point-topoint global path planner and sensor-based local navigator while a local map is constructed gradually by exploring the unknown terrain. The simulation studies demonstrate the proposed integrated methodology is efficient, effective, and robust.","PeriodicalId":186975,"journal":{"name":"2015 IEEE International Conference on Information and Automation","volume":"109 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Annealing-based guidance of a rescue robot for rescue mission with multi-goal navigation\",\"authors\":\"C. Luo, S. Furao, Simon X. Yang, Hongwei Mo\",\"doi\":\"10.1109/ICINFA.2015.7279406\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mission of a rescue robot is to search for some certain points and find trapped people or valuables to be rescued in an unknown terrain. A rescue robot should be able to be navigated to multiple goals. In this paper, a multi-goal navigation and mapping solution is found by simulated annealing (SA) based multi-goal navigation integrated a local navigator. The robot is guided by SA-based multi-goal route planner to search for multiple goals. Among goals, the robot is navigated by point-topoint global path planner and sensor-based local navigator while a local map is constructed gradually by exploring the unknown terrain. The simulation studies demonstrate the proposed integrated methodology is efficient, effective, and robust.\",\"PeriodicalId\":186975,\"journal\":{\"name\":\"2015 IEEE International Conference on Information and Automation\",\"volume\":\"109 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE International Conference on Information and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICINFA.2015.7279406\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Information and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICINFA.2015.7279406","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Annealing-based guidance of a rescue robot for rescue mission with multi-goal navigation
Mission of a rescue robot is to search for some certain points and find trapped people or valuables to be rescued in an unknown terrain. A rescue robot should be able to be navigated to multiple goals. In this paper, a multi-goal navigation and mapping solution is found by simulated annealing (SA) based multi-goal navigation integrated a local navigator. The robot is guided by SA-based multi-goal route planner to search for multiple goals. Among goals, the robot is navigated by point-topoint global path planner and sensor-based local navigator while a local map is constructed gradually by exploring the unknown terrain. The simulation studies demonstrate the proposed integrated methodology is efficient, effective, and robust.