基于近邻算法的无人机采集森林数据航迹路线的规划

Neighbor-based Trajectory Planning of Unmanned Aerial Vehicles for Data Collection in Forest

为提升数据采集效率,提出基于近邻算法的无人机数据采集航迹规划算法(Nearest Neighbor-based trajectory planning of UAVs for Data Collection, NNDC)。该算法允许无人机通过无线电能传输(Wireless Power Transfer, WPT)向节点补给能量,延长节点的工作时间。以无人机能耗和确保收集每个节点数据为约束条件,建立最小化数据采集时间的目标函数,利用近邻算法求解目标函数,获取无人机最优的数据采集航迹,实现对无人机航迹的规划。性能分析表明,相比于同类算法,NNDC算法降低了数据采集时间和数据采集阶段的无人机能耗。在节点数从6~20变化期间,NNDC算法采集所有节点数据的平均时间低于100 s。

In order to improve the efficiency of data collection, nearest neighbor-based trajectory planning of unmanned aerial vehicle(UAV) for data collection(NNDC) is proposed in this paper. In NNDC algorithm, energy of node is supplied through wireless power transfer(WPT) from UAV. Then the working time of node is extended. Based on the constraints of energy consumption of UAV and ensuring the collection data of each node, the objective function of minimizing time of collecting data is established, which is solved by nearest neighbor algorithm. Then, the optimal trajectory of collecting data is obtained to realize the UAV trajectory planning. Performance analysis shows that the proposed NNDC algorithm outperform the similar algorithm in terms of time of collecting data and energy consumption of UAV in data collection process. The average time of collecting data is less than 100 s when the number of nodes is from 6 to 20.