无人机斜面贴近摄影测量的三维航线规划研究

针对倾斜摄影测量对与水平面存在较大夹角的斜面目标,难以采集到有效影像数据这一问题,本文提出基于主成分分析(principal component analysis,PCA)算法的斜面贴近摄影测量三维航线规划方法。首先,利用PCA算法求取无人机的飞行方向与摄影机主光轴方向;其次,结合约束条件得到的航迹点间隔,计算出航迹点三维坐标与无人机姿态;最后,生成无人机航线文件并导入地面控制端飞行作业,实现斜面目标高分辨率影像数据自动采集。结果表明:通过本方法得到的三维航线布局工整,采集到的影像分布均匀,其重建的三维模型精度高、纹理细腻、几何完整性好;相较于倾斜摄影测量得到的模型,在点位相对精度、模型完整性、纹理精细度上得到了显著提升。

高原山地环境下无人机通视图航线规划方法研究——以香格里拉—奔子栏航线为例

高原山地环境山脉较高,普通无人机在航拍获取地震灾情时很难飞越大型山脉。通过对高原山地地震特征进行分析,阐述障碍物通视图的基本原理,并以香格里拉—奔子栏航线为例进行通视图航线规划,采用迪克斯屈拉(Dijkstra)算法求出航线起飞点到目标点的最短路径,最后利用Google earth软件绘制出最优航线。通视图航线规划为无人机飞越大型山脉或避开障碍物提供了一种较好的航线规划方法。

一种改进CPSO算法的无人机三维航线规划设计

针对基于混沌粒子群算法(CPSO)的航线规划在搜索过程中易陷入停滞和局部最优与多维计算时迭代速度慢的问题,通过引入Levy飞行随机扰动,建立数据交互的更新机制,加入高度、转角、耗能以及障碍物4个约束条件,提出一种改进混沌粒子群(ICPSO)算法,大大提高了更新最优解的概率。仿真结果表明,与传统粒子群优化(PSO)、灰狼优化(GWO)和鲸鱼优化(WO)三种算法相比,ICPSO算法在迭代速度、收敛准确性和有效性方面更强;其三维航线规划的距离最短,适应度最高。

无人机倾斜摄影测量构建悬索桥三维模型与病害检测——以邵阳市桂花大桥为例

为解决大型桥梁病害检测工作存在检测难度大、效率低的问题。以邵阳市桂花悬索大桥为实验对象,利用无人机(unmanned aerial vehicle,UAV)搭载单镜头相机,按照“井字飞行”和“环绕飞行”两种航线飞行模式进行倾斜摄影测量构建悬索桥三维实景模型。利用三维模型测绘软件EPS测量悬索桥特征点几何要素,进行悬索桥构件几何参数和病害的检测。实验结果表明:利用无人机倾斜摄影测量构建的三维实景模型纹理清晰,外观效果较好,还原了桥梁的真实形态。利用全站仪实测数据进行精度验证,“井字飞行”和“环绕飞行”两种模式构建的三维模型均具有较高的几何精度。“环绕飞行”模式相对于“井字飞行”模式在作业效率、影像数据量等方面具有明显优势。基于无人机倾斜摄影测量构建的桥梁三维实景模型能发现和定位显著的病害,可为其他工程应用提供借鉴和参考。

UAV trajectory planning algorithmfor data collection in wireless sensor networks

In order to maximize the value of information(VoI)of collected data in unmanned aerial vehicle(UAV)-aided wireless sensor networks(WSNs),a UAV trajectory planning algorithm named maximum VoI first and successive convex approximation(MVF-SCA)is proposed.First,the Rician channel model is adopted in the system and sensor nodes(SNs)are divided into key nodes and common nodes.Secondly,the data collection problem is formulated as a mixed integer non-linear program(MINLP)problem.The problem is divided into two sub-problems according to the different types of SNs to seek a sub-optimal solution with a low complexity.Finally,the MVF-SCA algorithm for UAV trajectory planning is proposed,which can not only be used for daily data collection in the target area,but also collect time-sensitive abnormal data in time when the exception occurs.Simulation results show that,compared with the existing classic traveling salesman problem(TSP)algorithm and greedy path planning algorithm,the VoI collected by the proposed algorithm can be improved by about 15%to 30%.

Multi-objective evolutionary approach for UAV cruise route planning to collect traffic information

Unmanned aerial vehicle(UAV)was introduced as a novel traffic device to collect road traffic information and its cruise route planning problem was considered.Firstly,a multi-objective optimization model was proposed aiming at minimizing the total cruise distance and the number of UAVs used,which used UAV maximum cruise distance,the number of UAVs available and time window of each monitored target as constraints.Then,a novel multi-objective evolutionary algorithm was proposed.Next,a case study with three time window scenarios was implemented.The results show that both the total cruise distance and the number of UAVs used continue to increase with the time window constraint becoming narrower.Compared with the initial optimal solutions,the optimal total cruise distance and the number of UAVs used fall by an average of 30.93% and 31.74%,respectively.Finally,some concerns using UAV to collect road traffic information were discussed.