{"title":"机器人路径规划的多策略方法","authors":"G. Bianco, R. Cassinis","doi":"10.1109/EURBOT.1996.551889","DOIUrl":null,"url":null,"abstract":"The paper presents a proposal for an autonomous robot path planning system that uses several strategies to reach a target also in an a-priori unknown environment. The proposed method has learning capabilities that allow the robot to take advantage of previous experience, thus improving its performance during successive traveling in the same environment. The proposed multistrategic approach has been tested both on a software simulator and on a real robot.","PeriodicalId":136786,"journal":{"name":"Proceedings of the First Euromicro Workshop on Advanced Mobile Robots (EUROBOT '96)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Multi-strategic approach for robot path planning\",\"authors\":\"G. Bianco, R. Cassinis\",\"doi\":\"10.1109/EURBOT.1996.551889\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents a proposal for an autonomous robot path planning system that uses several strategies to reach a target also in an a-priori unknown environment. The proposed method has learning capabilities that allow the robot to take advantage of previous experience, thus improving its performance during successive traveling in the same environment. The proposed multistrategic approach has been tested both on a software simulator and on a real robot.\",\"PeriodicalId\":136786,\"journal\":{\"name\":\"Proceedings of the First Euromicro Workshop on Advanced Mobile Robots (EUROBOT '96)\",\"volume\":\"58 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-10-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the First Euromicro Workshop on Advanced Mobile Robots (EUROBOT '96)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EURBOT.1996.551889\",\"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 of the First Euromicro Workshop on Advanced Mobile Robots (EUROBOT '96)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EURBOT.1996.551889","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The paper presents a proposal for an autonomous robot path planning system that uses several strategies to reach a target also in an a-priori unknown environment. The proposed method has learning capabilities that allow the robot to take advantage of previous experience, thus improving its performance during successive traveling in the same environment. The proposed multistrategic approach has been tested both on a software simulator and on a real robot.
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