无人机自动导航避开威胁区域

Arpit Gupta, Abhishek Gupta, C. Bocaniala, V. Sastry
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引用次数: 2

摘要

无人飞行器(UAV)被认为是未来的技术。避障是无人机高精度飞行中最具挑战性的任务之一。本文将障碍物视为一个球形威胁区域,采用几何方法开发避碰算法。该算法采用粒子群算法(PSO)对机动的最终参数进行求解。本文对PSO的有效性和原理进行了论证。用已有的求解非线性方程的数学工具对粒子群算法的结果进行了验证。比较了Mullerpsilas法、Newton-Raphsonpsilas自动微分法和符号微分法。利用Matlab对该算法进行了仿真。验证了该算法的准确性和简单性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Avoidance of threat zone by UAV for automated navigation
Unmanned air vehicles (UAV) are considered as technologies of future. Obstacle avoidance is one of the most challenging tasks which the UAV has to perform with high level of accuracy. In this paper, obstacle is considered as a spherical threat zone and a geometric approach is used to develop the algorithm to avoid the collision. The algorithm uses particle swarm optimization (PSO) to evaluate the final parameters of the maneuver. The efficacy and gist of PSO are justified in the paper. The results derived from PSO are verified with other existent mathematical tools to solve a non linear equation. The comparison is done with Mullerpsilas method, Newton-Raphsonpsilas method with Automatic Differentiation and Symbolic differentiation. The algorithm is simulated using Matlab. The level of accuracy and simplicity of the algorithm is demonstrated.
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