{"title":"全驱动自动驾驶地面车辆的实时路径规划*","authors":"R. Damerius, T. Jeinsch","doi":"10.1109/MED54222.2022.9837178","DOIUrl":null,"url":null,"abstract":"This paper presents a method for real-time path planning for fully actuated autonomous surface vehicles in confined waters. The goal is to continuously generate a collision-free path from a given initial pose to a given final pose. Both the own vehicle and static obstacles are represented as convex polygons. As soon as the environment changes, or other initial or final poses are specified, a warm start is performed, in which the results of previous solutions are reused. An optimal sampling-based approach is used to explore the search space. In a cost function, the length of the path is weighted together with the distance to all obstacles. Some parts of the cost function are calculated in advance and stored in look-up tables to reduce the computation time. The result is an optimal path from an initial pose to a final pose that avoids collisions of the vehicle with static obstacles. The proposed warm start procedure is tested by real-time experiments using different scenarios.","PeriodicalId":354557,"journal":{"name":"2022 30th Mediterranean Conference on Control and Automation (MED)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Real-Time Path Planning for Fully Actuated Autonomous Surface Vehicles*\",\"authors\":\"R. Damerius, T. Jeinsch\",\"doi\":\"10.1109/MED54222.2022.9837178\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a method for real-time path planning for fully actuated autonomous surface vehicles in confined waters. The goal is to continuously generate a collision-free path from a given initial pose to a given final pose. Both the own vehicle and static obstacles are represented as convex polygons. As soon as the environment changes, or other initial or final poses are specified, a warm start is performed, in which the results of previous solutions are reused. An optimal sampling-based approach is used to explore the search space. In a cost function, the length of the path is weighted together with the distance to all obstacles. Some parts of the cost function are calculated in advance and stored in look-up tables to reduce the computation time. The result is an optimal path from an initial pose to a final pose that avoids collisions of the vehicle with static obstacles. The proposed warm start procedure is tested by real-time experiments using different scenarios.\",\"PeriodicalId\":354557,\"journal\":{\"name\":\"2022 30th Mediterranean Conference on Control and Automation (MED)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 30th Mediterranean Conference on Control and Automation (MED)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MED54222.2022.9837178\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 30th Mediterranean Conference on Control and Automation (MED)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MED54222.2022.9837178","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Real-Time Path Planning for Fully Actuated Autonomous Surface Vehicles*
This paper presents a method for real-time path planning for fully actuated autonomous surface vehicles in confined waters. The goal is to continuously generate a collision-free path from a given initial pose to a given final pose. Both the own vehicle and static obstacles are represented as convex polygons. As soon as the environment changes, or other initial or final poses are specified, a warm start is performed, in which the results of previous solutions are reused. An optimal sampling-based approach is used to explore the search space. In a cost function, the length of the path is weighted together with the distance to all obstacles. Some parts of the cost function are calculated in advance and stored in look-up tables to reduce the computation time. The result is an optimal path from an initial pose to a final pose that avoids collisions of the vehicle with static obstacles. The proposed warm start procedure is tested by real-time experiments using different scenarios.