{"title":"基于在线优化的多辆无人车协调","authors":"R. Fierro, C. Branca, J. Spletzer","doi":"10.1109/ICNSC.2005.1461278","DOIUrl":null,"url":null,"abstract":"The objective of this work is to investigate on-line optimization-based coordination strategies for robot teams to efficiently accomplish a mission (e.g., reach a set of assigned targets) while avoiding collisions. The multi-robot coordination problem is addressed by solving an on-line receding-horizon mixed-integer program to find some suitable inputs for the vehicles. Simulations results verify the feasibility of our approach.","PeriodicalId":313251,"journal":{"name":"Proceedings. 2005 IEEE Networking, Sensing and Control, 2005.","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"On-line optimization-based coordination of multiple unmanned vehicles\",\"authors\":\"R. Fierro, C. Branca, J. Spletzer\",\"doi\":\"10.1109/ICNSC.2005.1461278\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The objective of this work is to investigate on-line optimization-based coordination strategies for robot teams to efficiently accomplish a mission (e.g., reach a set of assigned targets) while avoiding collisions. The multi-robot coordination problem is addressed by solving an on-line receding-horizon mixed-integer program to find some suitable inputs for the vehicles. Simulations results verify the feasibility of our approach.\",\"PeriodicalId\":313251,\"journal\":{\"name\":\"Proceedings. 2005 IEEE Networking, Sensing and Control, 2005.\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-03-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. 2005 IEEE Networking, Sensing and Control, 2005.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNSC.2005.1461278\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. 2005 IEEE Networking, Sensing and Control, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNSC.2005.1461278","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On-line optimization-based coordination of multiple unmanned vehicles
The objective of this work is to investigate on-line optimization-based coordination strategies for robot teams to efficiently accomplish a mission (e.g., reach a set of assigned targets) while avoiding collisions. The multi-robot coordination problem is addressed by solving an on-line receding-horizon mixed-integer program to find some suitable inputs for the vehicles. Simulations results verify the feasibility of our approach.