{"title":"基于改进动态窗口法的无人机穿越密集障碍物区域路径规划","authors":"Wenfei Wang, L. Ru, B. Lu, Shiguang Hu","doi":"10.1109/EEI59236.2023.10212936","DOIUrl":null,"url":null,"abstract":"With the continuous development and deepening of UAV research field, the demand for UAV navigation tasks is also increasing, and its path planning technology has gradually become an important part of UAV research and development. Aiming at the problem of path planning in local dense obstacle area of UAV, an improved dynamic window approach (DWA) is proposed. Aiming at the problem that DWA algorithm itself has fixed evaluation parameters and cannot effectively adapt to dense obstacle environment, combined with electric potential energy theory, the prediction trajectory selection mechanism is improved and the dynamic adjustment function of velocity parameters is designed. Finally, the feasibility and effectiveness of the improved DWA algorithm are proved by simulation experiments.","PeriodicalId":363603,"journal":{"name":"2023 5th International Conference on Electronic Engineering and Informatics (EEI)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Path Planning of UAV Crossing Dense Obstacle Area Based on Improved Dynamic Window Approach\",\"authors\":\"Wenfei Wang, L. Ru, B. Lu, Shiguang Hu\",\"doi\":\"10.1109/EEI59236.2023.10212936\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the continuous development and deepening of UAV research field, the demand for UAV navigation tasks is also increasing, and its path planning technology has gradually become an important part of UAV research and development. Aiming at the problem of path planning in local dense obstacle area of UAV, an improved dynamic window approach (DWA) is proposed. Aiming at the problem that DWA algorithm itself has fixed evaluation parameters and cannot effectively adapt to dense obstacle environment, combined with electric potential energy theory, the prediction trajectory selection mechanism is improved and the dynamic adjustment function of velocity parameters is designed. Finally, the feasibility and effectiveness of the improved DWA algorithm are proved by simulation experiments.\",\"PeriodicalId\":363603,\"journal\":{\"name\":\"2023 5th International Conference on Electronic Engineering and Informatics (EEI)\",\"volume\":\"59 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 5th International Conference on Electronic Engineering and Informatics (EEI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EEI59236.2023.10212936\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 5th International Conference on Electronic Engineering and Informatics (EEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EEI59236.2023.10212936","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Path Planning of UAV Crossing Dense Obstacle Area Based on Improved Dynamic Window Approach
With the continuous development and deepening of UAV research field, the demand for UAV navigation tasks is also increasing, and its path planning technology has gradually become an important part of UAV research and development. Aiming at the problem of path planning in local dense obstacle area of UAV, an improved dynamic window approach (DWA) is proposed. Aiming at the problem that DWA algorithm itself has fixed evaluation parameters and cannot effectively adapt to dense obstacle environment, combined with electric potential energy theory, the prediction trajectory selection mechanism is improved and the dynamic adjustment function of velocity parameters is designed. Finally, the feasibility and effectiveness of the improved DWA algorithm are proved by simulation experiments.