This paper considers a time-constrained data collection problem from a network of ground sensors located on uneven terrain by an Unmanned Aerial Vehicle(UAV),a typical Unmanned Aerial System(UAS).The ground sensors ha...This paper considers a time-constrained data collection problem from a network of ground sensors located on uneven terrain by an Unmanned Aerial Vehicle(UAV),a typical Unmanned Aerial System(UAS).The ground sensors harvest renewable energy and are equipped with batteries and data buffers.The ground sensor model takes into account sensor data buffer and battery limitations.An asymptotically globally optimal method of joint UAV 3D trajectory optimization and data transmission schedule is developed.The developed method maximizes the amount of data transmitted to the UAV without losses and too long delays and minimizes the propulsion energy of the UAV.The developed algorithm of optimal trajectory optimization and transmission scheduling is based on dynamic programming.Computer simulations demonstrate the effectiveness of the proposed algorithm.展开更多
基金funding from the Australian Government,via Grant No.AUSMURIB000001 associated with ONR MURI Grant No.N00014-19-1-2571。
文摘This paper considers a time-constrained data collection problem from a network of ground sensors located on uneven terrain by an Unmanned Aerial Vehicle(UAV),a typical Unmanned Aerial System(UAS).The ground sensors harvest renewable energy and are equipped with batteries and data buffers.The ground sensor model takes into account sensor data buffer and battery limitations.An asymptotically globally optimal method of joint UAV 3D trajectory optimization and data transmission schedule is developed.The developed method maximizes the amount of data transmitted to the UAV without losses and too long delays and minimizes the propulsion energy of the UAV.The developed algorithm of optimal trajectory optimization and transmission scheduling is based on dynamic programming.Computer simulations demonstrate the effectiveness of the proposed algorithm.
文摘在无线传感网络中引用无人机(Unmanned Aerial Vehicle,UAV)提升了网络寿命和数据传输率。然而,地面上无线的传感节点(Wireless Ground Sensors,WGSs)与UAVs间通信仍存在一些技术挑战。为此,提出基于唤醒无线电的能效数据收集(Wake-up Radio based-Energy efficiency Data Collection,WEDC)算法。WEDC算法先建立UAV和WGS的能耗模型,再依据UAV所收集的数据以及能耗构建效用函数,然后利用两元素优化(2-optimization,2-opt)算法求解,进而得到UAV收集数据的最优路径。仿真结果表明,WEDC算法提高了网络寿命,并优化了所收集数据的质量。
