Target Entrapment Based on Adaptive Transformation of Gene Regulatory Networks  

作　　者：Wenji Li Pengxiang Ren Zhaojun Wang Chaotao Guan Zhun Fan 

机构地区：[1]College of Engineering,Shantou University,Shantou 515000,China [2]Shenzhen Institute for Advanced Study,University of Electronic Science and Technology of China,Shenzhen 518000,China

出　　处：《Journal of Beijing Institute of Technology》2024年第5期389-398,共10页北京理工大学学报（英文版）

基　　金：supported in part by the National Science and Technol-ogy Major Project(No.2021ZD0111502);the National Nat-ural Science Foundation of China(Nos.62176147,62476163);the Science and Technology Planning Project of Guangdong Province of China(Nos.2022A1515110660,2021JC06X549);the STU Scientific Research Foundation for Talents(No.NTF21001);Guangdong Basic and Applied Basic Research Foundation(No.2023B1515120020)。

摘　　要：The complexity of unknown scenarios and the dynamics involved in target entrapment make designing control strategies for swarm robots a formidable task,which in turn impacts their efficiency in complex and dynamic settings.To address these challenges,this paper introduces an adaptive swarm robot entrapment control model grounded in the transformation of gene regulatory networks(AT-GRN).This innovative model enables swarm robots to dynamically adjust entrap-ment strategies by assessing current environmental conditions via real-time sensory data.Further-more,an improved motion control model for swarm robots is designed to dynamically shape the for-mation generated by the AT-GRN.Through two sets of rigorous experimental environments,the proposed model significantly enhances the trapping performance of swarm robots in complex envi-ronments,demonstrating remarkable adaptability and stability.

关 键 词：swarm robots target entrapment adaptive transformation gene regulatory networks 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]