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Binocular Vision-Based Autonomous Path Planning for UAVs in Unknown Outdoor Scenes

机译：基于双眼视觉的自主路径规划，在未知的户外场景中的无人机

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摘要

It is a classic task for Unmanned Aerial Vehicles (UAVs) to accomplish autonomous scene perception and path planning in unknown 3-D outdoor environments. This paper investigates the problems of obstacle avoidance and path planning using binocular vision system. During the UAV's flight, the binocular vision sensor is used to obtain the local environment information in real time, and the distribution of obstacles in the environment can also be analyzed with the depth images acquired by the binocular vision. Inspired by the idea of dynamic window algorithm, a 3-D path planning algorithm is proposed to convert the global path to the combination of a group of local paths by using a series of 3-D models of predefined local paths. According to the screening algorithm for the passable candidate paths, the UAV will select the optimal one to guide its flight. A series of experiments are conducted by using a quadrotor platform DJI M100 and experimental results show the validity of the proposed approach.
机译：它是无人驾驶飞行器（无人机）的经典任务，以实现未知的3-D室外环境中的自主场景感知和路径规划。本文研究了双目视觉系统的避免避免和路径规划问题。在UAV的飞行期间，双目视觉传感器用于实时获得本地环境信息，并且还可以利用由双目视觉获取的深度图像分析环境中的障碍物的分布。通过动态窗口算法思想的启发，一个3-d路径规划算法采用了一系列的预定义的本地路径3-d模式为全局路径转换为一组的本地路径的组合。根据可通过候选路径的筛选算法，UAV将选择最佳的最佳方法来引导其飞行。通过使用四射线平台DJI M100进行了一系列实验，实验结果表明了所提出的方法的有效性。

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