{"title":"The Free Path Planner Based on Windmill Decomposition","authors":"G. Jan, C. Luo, M. Lee, Hui-Ching Hsieh","doi":"10.1109/airc56195.2022.9836984","DOIUrl":null,"url":null,"abstract":"In this article, a new obstacle-avoidance path planner is proposed based on the windmill decomposition to find the shortest path in the Euclidean plane with rectangle obstacles. Using the Dijkstra's shortest path algorithm in a connected graph, this study constructs a windmill decomposition of the free space (obstacle avoidance space), and uses their centroids to plan the shortest free path from the start point to the end point. The advantage of this research is that, compared with other traditional algorithms, the time complexity of this algorithm is $O(n\\text{log}\\ n)$, and the free path for obstacle avoidance can be planned in a short time, where $n$ is the number of obstacles.","PeriodicalId":147463,"journal":{"name":"2022 3rd International Conference on Artificial Intelligence, Robotics and Control (AIRC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 3rd International Conference on Artificial Intelligence, Robotics and Control (AIRC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/airc56195.2022.9836984","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this article, a new obstacle-avoidance path planner is proposed based on the windmill decomposition to find the shortest path in the Euclidean plane with rectangle obstacles. Using the Dijkstra's shortest path algorithm in a connected graph, this study constructs a windmill decomposition of the free space (obstacle avoidance space), and uses their centroids to plan the shortest free path from the start point to the end point. The advantage of this research is that, compared with other traditional algorithms, the time complexity of this algorithm is $O(n\text{log}\ n)$, and the free path for obstacle avoidance can be planned in a short time, where $n$ is the number of obstacles.