Research And Implementation Of Unmanned Aerial Vehicle Coverage Path Planning Algorithm Under The Constraint Of Energy

Unmanned aerial vehicle(UAV)is one of the typical representatives of the intelligent unmanned systems,which is widely used among various fields to solve various problems due to their high mobility and high efficiency.The technology of coverage path planning(CPP)can be used in practical applications such as agricultural plant protection,mine inspections,rescue and disaster relief,and map reconstruction by UAVs.The area coverage is a classic problem of path planning,which aims at finding a path traverses all points in the target area while avoiding obstacles.If the limited energy of UAV is not considered when the target area is huge,the UAV may not completely cover the target area and even result in some unknown disasters.Therefore,considering the limited energy of UAV,this paper proposed a shadow-following(SF)algorithm for CPP by single-UAV,which improves the energy utilization of UAV.Then,this research extends the SF algorithm to multi-UAV and designs a load balanced(LB)algorithm to improves the coverage efficiency of UAVs.This paper carried out experimental verification for these two algorithms and built the prototype system based on the research.The main contributions of this article include the following three aspects:(1)Aiming at the problem that the UAV does not perform coverage during returning among the existing research considering the limited energy,which results in a decrease in the coverage efficiency,this paper proposed a shadow-following algorithm.The SF algorithm updates the shadow path while calculating the target position.The shadow path is adjacent to the covered area or obstacles,so that the UAV can return to the starting station along the shadow path and perform the coverage task.While satisfying the limited energy constraints of UAV and the integrity of uncovered area,the SF algorithm can improve the energy utilization of UAV and the completion efficiency of the coverage task.Considering the scene of the target area with multiple obstacles,this paper proposes to use the obstacle surrounding grid for calculating and updating of the shadow path,so that the shadow path can avoid obstacles while reducing the redundancy of the forward path,which improves the coverage efficiency and robustness of the SF algorithm.(2)Aiming at the uneven task distribution of the existing multi-UAV CPP algorithm considering limited energy,we propose a load balanced(LB)multi-UAV algorithm.The LB algorithm decouples the dual-objective optimization problem of the number and task load of UAVs.In the first step,the LB algorithm computes the minimize number of UAVs by improving the coverage efficiency of each UAV based on the SF algorithm.In the second step,the LB algorithm use the load balanced strategy to redivide the target area to allocate the subarea to each UAV,thereby improving the efficiency of multi-UAV in completing the coverage task.(3)Based on the above research results,this paper conducted the comparative experiment to verify the coverage effectiveness of the SF algorithm and the LB algorithm.In addition,this paper designs and implements a prototype system of UAV CPP algorithm considering the limited energy.This work designs the interface in the QT environment to realize the planning process of the SF and LB algorithm.