Density-Based Optimal UAV Path Planning for Photovoltaic Farm Inspection in Complex Topography

In order to improve power generation efficiency and reduce land cost, many large-scale photovoltaic (PV) farms are built on the mountain. The rugged terrain of the mountains leads to an irregular distribution of the PV modules’ location. Compared with manual inspection, the efficiency of unmanned aerial vehicles (UAVs) inspection is much higher. The path planning of scattered PV modules has become a challenge. In this paper, we use improved Density-Based Spatial Clustering of Applications with Noise (DBSACN) to partition the entire area. In order to reduce the number of turns of UAV, the partitions tend to divide the same row of PV modules into the same area. For the PV modules in each area, the full coverage path planning (CPP) of the boustrophedon will be adopted, and the lateral spacing between the PV modules can fly directly. Finally, the path control points are smoothed using Bezier Curves interpolation.

[1]  Mohammadreza Aghaei,et al.  Light Unmanned Aerial Vehicles (UAVs) for Cooperative Inspection of PV Plants , 2014, IEEE Journal of Photovoltaics.

[2]  Zhou Lu,et al.  Research about local path planning of moving robot based on improved artificial potential field , 2013, 2013 25th Chinese Control and Decision Conference (CCDC).

[3]  Xiu Yang,et al.  Path Planning and Following of Omnidirectional Mobile Robot Based on B-spline , 2018, 2018 Chinese Control And Decision Conference (CCDC).

[4]  Reagan L. Galvez,et al.  Path planning for quadrotor UAV using genetic algorithm , 2014, 2014 International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM).

[5]  Feifei Jiang,et al.  Performance Analysis of a Mountain Land PV Plant and a Water Surface PV Plant , 2017 .

[6]  Lin Xu,et al.  Global smooth path planning for mobile robots based on continuous Bezier curve , 2017, 2017 Chinese Automation Congress (CAC).

[7]  Vincent Roberge,et al.  Comparison of Parallel Genetic Algorithm and Particle Swarm Optimization for Real-Time UAV Path Planning , 2013, IEEE Transactions on Industrial Informatics.

[8]  Chang Che,et al.  A Brief Review of the Intelligent Algorithm for Traveling Salesman Problem in UAV Route Planning , 2019, 2019 IEEE 9th International Conference on Electronics Information and Emergency Communication (ICEIEC).

[9]  Chaomin Luo,et al.  Complete Coverage Autonomous Underwater Vehicles Path Planning Based on Glasius Bio-Inspired Neural Network Algorithm for Discrete and Centralized Programming , 2019, IEEE Transactions on Cognitive and Developmental Systems.

[10]  Eunjin Kim,et al.  A fuzzy adaptive differential evolution for multi-objective 3D UAV path optimization , 2017, 2017 IEEE Congress on Evolutionary Computation (CEC).

[11]  Xiaoguang Gao,et al.  UAV Path Planning Based on Bidirectional Sparse A* Search Algorithm , 2010, 2010 International Conference on Intelligent Computation Technology and Automation.

[12]  Abbas Harifi,et al.  UAV Path Planning for Data Gathering of IoT Nodes: Ant Colony or Simulated Annealing Optimization , 2019, 2019 3rd International Conference on Internet of Things and Applications (IoT).

[13]  Xu Miao,et al.  Scalable Coverage Path Planning for Cleaning Robots Using Rectangular Map Decomposition on Large Environments , 2018, IEEE Access.

[14]  Wu Jiang,et al.  Path planning for UAVS based on improved artificial potential field method through changing the repulsive potential function , 2016, 2016 IEEE Chinese Guidance, Navigation and Control Conference (CGNCC).

[15]  Qiang Wang,et al.  Three-dimensional path planning for UAV based on improved PSO algorithm , 2014, The 26th Chinese Control and Decision Conference (2014 CCDC).

[16]  Guangjie Han,et al.  An Improved Ant Colony Algorithm for Path Planning in One Scenic Area With Many Spots , 2017, IEEE Access.

[17]  Xiaojun Xing,et al.  Path planning for UAV tracking target based on improved A-star algorithm , 2019, 2019 1st International Conference on Industrial Artificial Intelligence (IAI).

[18]  Xia Chen,et al.  The UAV dynamic path planning algorithm research based on Voronoi diagram , 2014, The 26th Chinese Control and Decision Conference (2014 CCDC).