Efficient multiple unmanned aerial vehicles(UAVs)path planning is crucial for improving mission completion efficiency in UAV operations.However,during the actual flight of UAVs,the flight time between nodes is always ...Efficient multiple unmanned aerial vehicles(UAVs)path planning is crucial for improving mission completion efficiency in UAV operations.However,during the actual flight of UAVs,the flight time between nodes is always influenced by external factors,making the original path planning solution ineffective.In this paper,the multi-depot multi-UAV path planning problem with uncertain flight time is modeled as a robust optimization model with a budget uncertainty set.Then,the robust optimization model is transformed into a mixed integer linear programming model by the strong duality theorem,which makes the problem easy to solve.To effectively solve large-scale instances,a simulated annealing algorithm with a robust feasibility check(SA-RFC)is developed.The numerical experiment shows that the SA-RFC can find high-quality solutions within a few seconds.Moreover,the effect of the task location distribution,depot counts,and variations in robustness parameters on the robust optimization solution is analyzed by using Monte Carlo experiments.The results demonstrate that the proposed robust model can effectively reduce the risk of the UAV failing to return to the depot without significantly compromising the profit.展开更多
面向无人机智能巡检的桥梁数字孪生系统需要集成与处理增量式的多模态数据,以支撑面向现实场景动态决策的高精度仿真需求。然而,现有数字孪生平台时空数据管理割裂、多模态数据融合不足、决策交互机制缺失,并未形成真正意义上的面向无...面向无人机智能巡检的桥梁数字孪生系统需要集成与处理增量式的多模态数据,以支撑面向现实场景动态决策的高精度仿真需求。然而,现有数字孪生平台时空数据管理割裂、多模态数据融合不足、决策交互机制缺失,并未形成真正意义上的面向无人机智能巡检的桥梁数字孪生系统。基于此,提出了一种融合IFC (Industry Foundation Classes)、知识图谱和游戏引擎的桥梁数字孪生系统。系统以基于IFC构建的知识图谱(IFC-graph)为核心的数据管理引擎,统一整合桥梁设计建造信息、无人机巡检规划所需的结构语义,以及巡检过程中获取的多模态感知数据(如点云、图像等),构建覆盖构件-子结构-区域等多空间尺度、支持全生命周期演化的增量式语义管理体系,并实现语义驱动下的高效信息检索与动态数据关联。在虚拟仿真层面,系统引入虚幻引擎构建高保真三维桥梁环境,精准复刻物理场景中的几何结构与环境要素,并通过与IFC知识图谱的双向联动机制,支持无人机路径规划、飞行策略模拟与多轮次巡检任务的交互式推演,能够真实还原飞行过程中的转向、避障与碰撞等复杂行为。基于上述系统框架,进一步提出一种融合构件语义的无人机巡检路径优化算法,有效提升路径规划的适应性与精度,实现面向关键构件的高分辨率检测。系统已在实际桥梁案例中完成部署与验证,结果表明:该方案具备良好的可扩展性与工程适用性,可为桥梁运维过程中的智能化分析与全生命周期管理提供新型解决思路与技术支撑。展开更多
基金supported by the National Natural Science Foundation of China(72571094,72271076,71871079)。
文摘Efficient multiple unmanned aerial vehicles(UAVs)path planning is crucial for improving mission completion efficiency in UAV operations.However,during the actual flight of UAVs,the flight time between nodes is always influenced by external factors,making the original path planning solution ineffective.In this paper,the multi-depot multi-UAV path planning problem with uncertain flight time is modeled as a robust optimization model with a budget uncertainty set.Then,the robust optimization model is transformed into a mixed integer linear programming model by the strong duality theorem,which makes the problem easy to solve.To effectively solve large-scale instances,a simulated annealing algorithm with a robust feasibility check(SA-RFC)is developed.The numerical experiment shows that the SA-RFC can find high-quality solutions within a few seconds.Moreover,the effect of the task location distribution,depot counts,and variations in robustness parameters on the robust optimization solution is analyzed by using Monte Carlo experiments.The results demonstrate that the proposed robust model can effectively reduce the risk of the UAV failing to return to the depot without significantly compromising the profit.
文摘面向无人机智能巡检的桥梁数字孪生系统需要集成与处理增量式的多模态数据,以支撑面向现实场景动态决策的高精度仿真需求。然而,现有数字孪生平台时空数据管理割裂、多模态数据融合不足、决策交互机制缺失,并未形成真正意义上的面向无人机智能巡检的桥梁数字孪生系统。基于此,提出了一种融合IFC (Industry Foundation Classes)、知识图谱和游戏引擎的桥梁数字孪生系统。系统以基于IFC构建的知识图谱(IFC-graph)为核心的数据管理引擎,统一整合桥梁设计建造信息、无人机巡检规划所需的结构语义,以及巡检过程中获取的多模态感知数据(如点云、图像等),构建覆盖构件-子结构-区域等多空间尺度、支持全生命周期演化的增量式语义管理体系,并实现语义驱动下的高效信息检索与动态数据关联。在虚拟仿真层面,系统引入虚幻引擎构建高保真三维桥梁环境,精准复刻物理场景中的几何结构与环境要素,并通过与IFC知识图谱的双向联动机制,支持无人机路径规划、飞行策略模拟与多轮次巡检任务的交互式推演,能够真实还原飞行过程中的转向、避障与碰撞等复杂行为。基于上述系统框架,进一步提出一种融合构件语义的无人机巡检路径优化算法,有效提升路径规划的适应性与精度,实现面向关键构件的高分辨率检测。系统已在实际桥梁案例中完成部署与验证,结果表明:该方案具备良好的可扩展性与工程适用性,可为桥梁运维过程中的智能化分析与全生命周期管理提供新型解决思路与技术支撑。
