非确定环境下基于分层理论多无人机动态协同设计

针对非确定环境下多无人机自主协同控制这一多约束、强耦合非线性优化问题，采用分层理论将其分解成三个相对独立子 层，即协同感知层、环境态势理解层和协同全局重规划层. 协同感知层借助“层协作感知”算子来进行多模信息融合，解决非确定环境下目 标（包括静态确定目标和动态非确定目标）的感知与识别；环境态势理解层则是解决动态非确定环境更新，以及基于窗口势场法的障碍物（威胁目标）规避问题；而协同全局重规划层则是利用“层场景引擎”来实现多机非确定环境下的自主协同、路径快速寻优及状态决策. 模拟结果显示构建的多机自主协同模型能较好地解决非确定环境下的路径寻优和状态决策问题.

Design of hierarchical theory based module for multiple unmanned air vehicles cooperation under uncertain environment

In the paper, a hierarchical theory based cooperation module with 3 layers, named cooperative sensing-, situation comprehending-, and global replanning-layer, is introduced to address the problem of multiple unmanned air vehicles (MUAVs) dynamic cooperation under uncertain environment. Specifically, a layer cooperative operator (LCO) is proposed for the purpose of target sensing and recognition, and window optimized potential field (WOPF) strategy is adopted for obstacle avoidance and environment adaption consideration, while layer sense engine operator (LSEO) is suggested to enhance the module's ability of global replanning and MUAVs trajectory optimization. Simulation results indicate the promising potential of our proposed module in the area of MUAVs autonomous cooperation under uncertain environment.