C. Vargas, J. S. Cansino, E. S. E. Quesada, L. G. Carrillo, L. Ramos-Velasco, R. Lozano
{"title":"Design and Implementation of an Artificial Neural Network Wavelet for Load Transportation with two Unmanned Aircraft Systems","authors":"C. Vargas, J. S. Cansino, E. S. E. Quesada, L. G. Carrillo, L. Ramos-Velasco, R. Lozano","doi":"10.1109/ICUAS.2019.8798097","DOIUrl":null,"url":null,"abstract":"This paper deals with the problem of enabling a team of two Unmanned Aircraft Systems to perform an autonomous load transportation task. We propose a strategy whose main objective is to ensure a stable flight of the team of agents when cooperatively transporting the load. The strategy is based on the implementation of a neural network controller and a neural network estimator, using wavelet activation functions in combination with a cooperative multi-agent control approach. To show the effectiveness and applicability of the proposed framework, a real time experimental implementation is presented. Additionally, a comparison with respect to a classic control law is also provided, demonstrating the superior performance attained when adopting the proposed controller.","PeriodicalId":426616,"journal":{"name":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICUAS.2019.8798097","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 paper deals with the problem of enabling a team of two Unmanned Aircraft Systems to perform an autonomous load transportation task. We propose a strategy whose main objective is to ensure a stable flight of the team of agents when cooperatively transporting the load. The strategy is based on the implementation of a neural network controller and a neural network estimator, using wavelet activation functions in combination with a cooperative multi-agent control approach. To show the effectiveness and applicability of the proposed framework, a real time experimental implementation is presented. Additionally, a comparison with respect to a classic control law is also provided, demonstrating the superior performance attained when adopting the proposed controller.