In light of the intricate and volatile nature of battlefield environments,unmanned aerial vehicle(UAV)swarms have become a critical asset in contemporary military operations.The autonomous obstacle avoidance capabilit...In light of the intricate and volatile nature of battlefield environments,unmanned aerial vehicle(UAV)swarms have become a critical asset in contemporary military operations.The autonomous obstacle avoidance capabilities of UAV swarms are crucial for enhancing their operational effectiveness and survivability in complex battlefield conditions.Consequently,this technology has garnered significant attention from researchers globally,positioning it as a key area of advanced military technology.In response to the diverse characteristics of obstacles in combat environments,a cooperative obstacle avoidance strategy for UAV swarms on the basis of an improved artificial potential field(APF)method and a variable topology structure is proposed in this study.By considering the properties of static and dynamic obstacles on the battlefield,the proposed strategy models the flight space with obstacles as being segmented into multiple smaller navigable regions between these obstacles.To address the limitations of the traditional APF method,this study introduces velocity adaptation components,angle factors,and auxiliary traction forces to optimize the repulsive force component of the traditional APF method.Additionally,combining this approach with a coalition-based variable topology formation reconfiguration algorithm,the strategy realizes autonomous obstacle avoidance for UAV swarms in battlefield obstacle environments.This method not only resolves the common issue of local minima in traditional APF obstacle avoidance techniques but also ensures effective obstacle avoidance by UAV swarms when large obstacles are encountered.The results of simulation experiments demonstrate the feasibility and performance of the proposed strategy.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.72471204)。
文摘In light of the intricate and volatile nature of battlefield environments,unmanned aerial vehicle(UAV)swarms have become a critical asset in contemporary military operations.The autonomous obstacle avoidance capabilities of UAV swarms are crucial for enhancing their operational effectiveness and survivability in complex battlefield conditions.Consequently,this technology has garnered significant attention from researchers globally,positioning it as a key area of advanced military technology.In response to the diverse characteristics of obstacles in combat environments,a cooperative obstacle avoidance strategy for UAV swarms on the basis of an improved artificial potential field(APF)method and a variable topology structure is proposed in this study.By considering the properties of static and dynamic obstacles on the battlefield,the proposed strategy models the flight space with obstacles as being segmented into multiple smaller navigable regions between these obstacles.To address the limitations of the traditional APF method,this study introduces velocity adaptation components,angle factors,and auxiliary traction forces to optimize the repulsive force component of the traditional APF method.Additionally,combining this approach with a coalition-based variable topology formation reconfiguration algorithm,the strategy realizes autonomous obstacle avoidance for UAV swarms in battlefield obstacle environments.This method not only resolves the common issue of local minima in traditional APF obstacle avoidance techniques but also ensures effective obstacle avoidance by UAV swarms when large obstacles are encountered.The results of simulation experiments demonstrate the feasibility and performance of the proposed strategy.
