{"title":"Path Planning Model of Intelligent Robot based on Computer Vision Recognition Algorithm","authors":"Xiaolei Zhang, Xiaotao Zhang","doi":"10.1109/ICICT57646.2023.10133975","DOIUrl":null,"url":null,"abstract":"This study has designed a path planning model for intelligent robot based on computer vision recognition algorithm. Here, the redundant nodes present in the pre-planned path are removed through the node screening mechanism, and the later the artificial potential field method is introduced to ensure that a safe distance is always maintained from the unknown obstacles present in the re-planning process. At the same time, this research study adopts the method of setting virtual target points to solve the local extreme value problem that may be encountered in the actual movement of the machine. For developing an efficient and intelligent path planning model, the computer vision should be referred. The binocular recognition is equipped with two symmetrical signal acquisition cameras, which can realize the positioning of the status information. The enhanced theoretical vision algorithm is then combined for performing systematic optimization. The performance is validated by testing it on different datasets.","PeriodicalId":126489,"journal":{"name":"2023 International Conference on Inventive Computation Technologies (ICICT)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Inventive Computation Technologies (ICICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICT57646.2023.10133975","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
This study has designed a path planning model for intelligent robot based on computer vision recognition algorithm. Here, the redundant nodes present in the pre-planned path are removed through the node screening mechanism, and the later the artificial potential field method is introduced to ensure that a safe distance is always maintained from the unknown obstacles present in the re-planning process. At the same time, this research study adopts the method of setting virtual target points to solve the local extreme value problem that may be encountered in the actual movement of the machine. For developing an efficient and intelligent path planning model, the computer vision should be referred. The binocular recognition is equipped with two symmetrical signal acquisition cameras, which can realize the positioning of the status information. The enhanced theoretical vision algorithm is then combined for performing systematic optimization. The performance is validated by testing it on different datasets.