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Vision Based Obstacle Detection and Avoidance for UAVs Using Image Segmentation

机译:基于视觉的无人机无人机图像障碍物检测与避免

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The present work proposes a vision based guidance scheme for an unmanned aerial vehicle (UAV) navigating through urban environments. Optical flow of image feature is considered to segment obstacles from the image. With the segmented obstacles, a collision cone based guidance law is proposed for avoidance. Detecting open space between segmented obstacles, a passage following guidance law is also presented for intelligent decision making. Simulations are carried out in a 3D environments created in VRML toolbox of MATLAB~®. Results shows a much improved performance as compared to existing optical flow based obstacle avoidance methods.
机译:本工作为在城市环境中航行的无人机提出了一种基于视觉的制导方案。图像特征的光流被认为可以分割图像中的障碍物。针对分段的障碍物,提出了一种基于碰撞锥的制导律以避免。检测分段的障碍物之间的开放空间时,还应遵循引导规律提供一条通道,以进行智能决策。在MATLAB〜®的VRML工具箱中创建的3D环境中进行仿真。与现有的基于光流的避障方法相比,结果表明性能大大提高。

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