运动规划
避碰
计算机科学
弹道
路径(计算)
避障
碰撞
障碍物
Dijkstra算法
实时计算
过程(计算)
方案(数学)
职位(财务)
MATLAB语言
模拟
最短路径问题
机器人
移动机器人
人工智能
图形
数学
计算机安全
操作系统
理论计算机科学
政治学
程序设计语言
物理
财务
天文
经济
法学
数学分析
作者
Nouman Bashir,Saâdi Boudjit,Gabriel Dauphin,Sherali Zeadally
标识
DOI:10.1016/j.simpat.2023.102815
摘要
The recent pandemic of COVID-19 has proven to be a test case for Unmanned Aerial Vehicles (UAVs). UAVs have shown great potential for plenty of applications in the face of this pandemic, but their scope of applications becomes limited due to the dependency on ground pilots. Irrespective of the application, it is imperative to have an autonomous path planning to utilize UAVs to their full potential. Collision-free trajectories are expected from the path planning process to ensure the safety of UAVs and humans on the ground. This work proposes a path planning technique where collision avoidance is mathematically proven under an uncertainty prerequisite, that the UAV follows its requested moving position within some threshold distance. This scheme ensures UAV safety by considering the underlying control’s system overshoots. Obstacles play a guiding role in selecting collision-free trajectories. These obstacles are modeled as rectangular shapes with interest points defined around their corners. These points further define collision-free permissible edges, and later we apply the Dijkstra algorithm to these edges before having the desired trajectory. Regardless of the size of deployment area, our proposed scheme incurs low computational load due to the dependency on pre-defined interest points only thereby making it suitable for real-time path planning. Simulation results obtained using MATLAB’s UAV Toolbox show that the proposed method succeeds in getting short collision-free trajectories.
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