地形
航路点
计算机科学
粒子群优化
运动规划
插值(计算机图形学)
趋同(经济学)
过程(计算)
运动学
模拟
人工智能
实时计算
算法
机器人
地理
运动(物理)
地图学
物理
经典力学
经济增长
经济
操作系统
作者
Jinbiao Yuan,Zhenbao Liu,Xiaoyu Xiong,Yunfeng Ai,Long Chen,Bin Tian
出处
期刊:IEEE transactions on intelligent vehicles
[Institute of Electrical and Electronics Engineers]
日期:2024-01-01
卷期号:9 (1): 1189-1203
标识
DOI:10.1109/tiv.2023.3307217
摘要
A global path planning method constrained by dynamics, kinematics, and terrain is proposed for Vertical Takeoff and Landing (VTOL) Unmanned Aerial Vehicles (UAVs). Firstly, new constant-altitude waypoints are interpolated above the terrain based on altitude information and terrain resolution. Account for the coverage of airborne sensors over the surface area, a horizontal waypoint interpolation optimization (HOPT) is performed at positions with excessive bending in the horizontal direction. Secondly, for vertical plane optimization (VOPT), i.e., height optimization, a Soft Actor-Critic-based Particle Swarm Optimization (SAC-PSO) is employed to optimize the convergence speed of the method and achieve terrain following (TF). Thirdly, to evaluate the generated paths, a deep residual network (DRSN) is designed to mitigate the impact of optimization failures during the iteration process and improve the stability of the algorithm. Simulation experiments demonstrate the efficiency and path quality of the proposed method, while real-world tasks validate its practicality.
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