J. Franco-Robles, J. Escareño, D. Soto-Guerrero, O. Labbani-Igbida
{"title":"Feedforward Formation Control based on Self-Organized Body-Schema","authors":"J. Franco-Robles, J. Escareño, D. Soto-Guerrero, O. Labbani-Igbida","doi":"10.1109/ICUAS51884.2021.9476689","DOIUrl":null,"url":null,"abstract":"In this paper we propose a new architecture of the self-organized body schema (SO-BoS) system capable of learning the configuration space of three rotorcrafts relative to a single sensor space. The SO-BoS cortical map architecture represents the posterior parietal cortex where sensory-motor of the human posture is synthesized (circular-reaction); we inspired on such process to control the displacement in formation of three rotorcraft UAVs. The SO-BoS-based feedforward control drives the aerial robots formation towards the desired position while avoiding obstacles and inter-agent collisions. The proposed strategy is a promising approach for aerial vehicles systems due to the plasticity resulting from the learning-babbling stage. A numerical result section is given to provide the inherent discussions to assess the effectiveness of the proposed intelligent navigation scheme.","PeriodicalId":423195,"journal":{"name":"2021 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"1 5","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Unmanned Aircraft Systems (ICUAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICUAS51884.2021.9476689","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this paper we propose a new architecture of the self-organized body schema (SO-BoS) system capable of learning the configuration space of three rotorcrafts relative to a single sensor space. The SO-BoS cortical map architecture represents the posterior parietal cortex where sensory-motor of the human posture is synthesized (circular-reaction); we inspired on such process to control the displacement in formation of three rotorcraft UAVs. The SO-BoS-based feedforward control drives the aerial robots formation towards the desired position while avoiding obstacles and inter-agent collisions. The proposed strategy is a promising approach for aerial vehicles systems due to the plasticity resulting from the learning-babbling stage. A numerical result section is given to provide the inherent discussions to assess the effectiveness of the proposed intelligent navigation scheme.