Maryam Khazaei Pool, Carlos Diaz Alvarenga, Marcelo Kallmann
{"title":"Path Smoothing with Deterministic Shortcuts","authors":"Maryam Khazaei Pool, Carlos Diaz Alvarenga, Marcelo Kallmann","doi":"10.1109/IRC55401.2022.00078","DOIUrl":null,"url":null,"abstract":"Path smoothing is an important operation in a number of path planning applications. While several approaches have been proposed in the literature, a lack of simple and effective methods with quality-based termination conditions can be observed. In this paper we propose a deterministic shortcut-based smoothing method that is simple to be implemented and achieves user-specified termination conditions based on solution quality, overcoming one of the main limitations observed in traditional random-based approaches. We present several benchmarks demonstrating that our method produces higher-quality results when compared to the traditional random shortcuts approach.","PeriodicalId":282759,"journal":{"name":"2022 Sixth IEEE International Conference on Robotic Computing (IRC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Sixth IEEE International Conference on Robotic Computing (IRC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IRC55401.2022.00078","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
Path smoothing is an important operation in a number of path planning applications. While several approaches have been proposed in the literature, a lack of simple and effective methods with quality-based termination conditions can be observed. In this paper we propose a deterministic shortcut-based smoothing method that is simple to be implemented and achieves user-specified termination conditions based on solution quality, overcoming one of the main limitations observed in traditional random-based approaches. We present several benchmarks demonstrating that our method produces higher-quality results when compared to the traditional random shortcuts approach.