We consider a scenario where an unmanned aerial vehicle(UAV),a typical unmanned aerial system(UAS),transmits confidential data to a moving ground target in the presence of multiple eavesdroppers.Multiple friendly reco...We consider a scenario where an unmanned aerial vehicle(UAV),a typical unmanned aerial system(UAS),transmits confidential data to a moving ground target in the presence of multiple eavesdroppers.Multiple friendly reconfigurable intelligent surfaces(RISs) help to secure the UAV-target communication and improve the energy efficiency of the UAV.We formulate an optimization problem to minimize the energy consumption of the UAV,subject to the mobility constraint of the UAV and that the achievable secrecy rate at the target is over a given threshold.We present an online planning method following the framework of model predictive control(MPC) to jointly optimize the motion of the UAV and the configurations of the RISs.The effectiveness of the proposed method is validated via computer simulations.展开更多
针对无人机编队内避碰问题,提出一种可实时机间避碰以及多碰撞冲突管理的多无人机协同航迹规划方案。通过对UAV编队避碰问题进行分析,采用分布式模型预测控制(decentralized model predictive control,DMPC)方法,将其转换为滚动在线优...针对无人机编队内避碰问题,提出一种可实时机间避碰以及多碰撞冲突管理的多无人机协同航迹规划方案。通过对UAV编队避碰问题进行分析,采用分布式模型预测控制(decentralized model predictive control,DMPC)方法,将其转换为滚动在线优化问题。设计了避碰管理单元,采用交互图更新机制解决多碰撞管理问题,运用基于角度变化的协同避碰规则,解决了分布式避碰问题的动作一致性问题。仿真结果表明,该方案可以有效解决4架无人机间多碰撞冲突问题,同时代价更小。展开更多
基金funding from the Australian Government,via grant AUSMURIB000001 associated with ONR MURI Grant N00014-19-1-2571。
文摘We consider a scenario where an unmanned aerial vehicle(UAV),a typical unmanned aerial system(UAS),transmits confidential data to a moving ground target in the presence of multiple eavesdroppers.Multiple friendly reconfigurable intelligent surfaces(RISs) help to secure the UAV-target communication and improve the energy efficiency of the UAV.We formulate an optimization problem to minimize the energy consumption of the UAV,subject to the mobility constraint of the UAV and that the achievable secrecy rate at the target is over a given threshold.We present an online planning method following the framework of model predictive control(MPC) to jointly optimize the motion of the UAV and the configurations of the RISs.The effectiveness of the proposed method is validated via computer simulations.
文摘针对无人机编队内避碰问题,提出一种可实时机间避碰以及多碰撞冲突管理的多无人机协同航迹规划方案。通过对UAV编队避碰问题进行分析,采用分布式模型预测控制(decentralized model predictive control,DMPC)方法,将其转换为滚动在线优化问题。设计了避碰管理单元,采用交互图更新机制解决多碰撞管理问题,运用基于角度变化的协同避碰规则,解决了分布式避碰问题的动作一致性问题。仿真结果表明,该方案可以有效解决4架无人机间多碰撞冲突问题,同时代价更小。
