基于深度神经网络的计算机视觉技术在路径规划中的应用研究

Application Research of Computer Vision Technology Based on Deep Neural Network in Path Planning

路径规划技术具有巨大的科研价值和广阔的应用前景,其在高科技领域的应用包括无人机的避障飞行、无人机飞行过程中的最优路径选择。计算机视觉技术可以对图片或视频进行处理,获取对应场景的多维信息,经过进一步的处理得到更加有效的信息。文章探析现有的基于深度神经网络的计算机视觉算法的原理、优缺点,对现有的计算机视觉算法进行优化,并将计算机视觉问题的解决方法应用到强化学习控制算法中,提高无人机路径规划的精度和效率。

Path planning technology has great scientific research value and broad application prospects.Its applications in high-tech fields include obstacle avoidance flight of UAV and optimal path selection in the flight process of UAV.Computer vision technology can process pictures or videos,obtain the multi-dimensional information of the corresponding scene,and get more effective information after further processing.This paper analyzes the principle,advantages and disadvantages of the existing computer vision algorithm based on deep neural network,optimizes the existing computer vision algorithm,and applies the solution of computer vision problems to the reinforcement learning control algorithm to improve the accuracy and efficiency of UAV path planning.