{"title":"On the real-time receding horizon control in harbor defense","authors":"Seungho Lee, G. Dullerud, E. Polak","doi":"10.1109/ACC.2015.7171889","DOIUrl":null,"url":null,"abstract":"In this paper, we develop an receding horizon control (RHC) law for controlling the pursuers in a pursuit-evasion problem arising in a harbor defense scenario and describe its real-time implementation that we apply experimentally to a robotic testbed. Our implementation of the RHC law makes use of a min-max formulation of the underlying optimal problem that must be solved at each sample time, which is solved using the method of outer approximations in conjunction with a phase I-phase II method of feasible directions, in conjunction with a network layer that abstracts each agent. We demonstrate the effectiveness of our implementation using real-time human-computer simulations, and human-robot interaction using a physical testbed comprised of model-sized hovercraft.","PeriodicalId":223665,"journal":{"name":"2015 American Control Conference (ACC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 American Control Conference (ACC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACC.2015.7171889","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
In this paper, we develop an receding horizon control (RHC) law for controlling the pursuers in a pursuit-evasion problem arising in a harbor defense scenario and describe its real-time implementation that we apply experimentally to a robotic testbed. Our implementation of the RHC law makes use of a min-max formulation of the underlying optimal problem that must be solved at each sample time, which is solved using the method of outer approximations in conjunction with a phase I-phase II method of feasible directions, in conjunction with a network layer that abstracts each agent. We demonstrate the effectiveness of our implementation using real-time human-computer simulations, and human-robot interaction using a physical testbed comprised of model-sized hovercraft.