{"title":"Hybrid FA-GA Controller for Path Planning of Mobile Robot","authors":"B. Patle, N. Pagar, D. Parhi, S. Sanap","doi":"10.1109/ICICCSP53532.2022.9862422","DOIUrl":null,"url":null,"abstract":"Recently, in the path planning of mobile robots, navigation in complex areas are still a challenging task using different AI techniques. One such problem of navigation is solved here using the firefly algorithm and the genetic algorithm as a hybrid approach. The proposed approach efficiently handles the sensory information and converts this into taking the accurate decision for solving the challenges of navigation such as obstacle avoidance and target seeking in a static environment. The proposed approach not only ensures path safety but also ensures path optimality on account of navigational parameters such as path length and navigational time. The developed approach has been tested in the simulation environment using the MATLAB software and in the real-time environment using the Khepera robot. The simulation and real-time results in presence of multiple obstacles are presented for the validation of the proposed FA-GA hybrid controller and obtained results are satisfactory in terms of path optimization.","PeriodicalId":326163,"journal":{"name":"2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICCSP53532.2022.9862422","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
Recently, in the path planning of mobile robots, navigation in complex areas are still a challenging task using different AI techniques. One such problem of navigation is solved here using the firefly algorithm and the genetic algorithm as a hybrid approach. The proposed approach efficiently handles the sensory information and converts this into taking the accurate decision for solving the challenges of navigation such as obstacle avoidance and target seeking in a static environment. The proposed approach not only ensures path safety but also ensures path optimality on account of navigational parameters such as path length and navigational time. The developed approach has been tested in the simulation environment using the MATLAB software and in the real-time environment using the Khepera robot. The simulation and real-time results in presence of multiple obstacles are presented for the validation of the proposed FA-GA hybrid controller and obtained results are satisfactory in terms of path optimization.