{"title":"运动规划的两级搜索算法","authors":"Pekka Isto","doi":"10.1109/ROBOT.1997.619170","DOIUrl":null,"url":null,"abstract":"A two-level search algorithm for motion planning is presented in this paper. The algorithm combines a multiheuristic local search algorithm with a subgoal graph based global guidance. A novel feature of the planner is that it can adjust the balance between local and global planning. As the experimental data suggests that the optimal balance depends on the problem, a scheduling mechanism is added to the algorithm to adjust the balance during planning. The resulting motion planner is capable of solving very difficult motion planning problems.","PeriodicalId":225473,"journal":{"name":"Proceedings of International Conference on Robotics and Automation","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"A two-level search algorithm for motion planning\",\"authors\":\"Pekka Isto\",\"doi\":\"10.1109/ROBOT.1997.619170\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A two-level search algorithm for motion planning is presented in this paper. The algorithm combines a multiheuristic local search algorithm with a subgoal graph based global guidance. A novel feature of the planner is that it can adjust the balance between local and global planning. As the experimental data suggests that the optimal balance depends on the problem, a scheduling mechanism is added to the algorithm to adjust the balance during planning. The resulting motion planner is capable of solving very difficult motion planning problems.\",\"PeriodicalId\":225473,\"journal\":{\"name\":\"Proceedings of International Conference on Robotics and Automation\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-04-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of International Conference on Robotics and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ROBOT.1997.619170\",\"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 International Conference on Robotics and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROBOT.1997.619170","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A two-level search algorithm for motion planning is presented in this paper. The algorithm combines a multiheuristic local search algorithm with a subgoal graph based global guidance. A novel feature of the planner is that it can adjust the balance between local and global planning. As the experimental data suggests that the optimal balance depends on the problem, a scheduling mechanism is added to the algorithm to adjust the balance during planning. The resulting motion planner is capable of solving very difficult motion planning problems.
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