Research on the recovery system of the fixed wing swarm based on the robotic vision in the marine environment

Renjie Yu, Qi Li, Decai Li, Yuqing He
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Abstract

The use of the robotic arm to achieve the recovery of the unmanned aerial vehicles(UAV) has a broad applications in the marine environment; however, due to the complexity of the marine environment(such as the cloud and snow weather, and the high light intensity), in the process of the recovery of the UAVs, the relative position relationship between the robotic arm and the UAV can not be accurately reflected based on the existing methods of the machine vision. In this work, the visual recognition algorithm based on the aruco code of the binocular camera is proposed to solve the above problem. Firstly the median filtering process is added to eliminate the salt and pepper noise in the process of the visual recognition of the two-dimensional code. Then, a new binary conversion method is carried out to obtain the accurate relative position between the robotic arm and the UAV. Finally, based on the information of the relative position, the robotic arm carries out the path planning and the control to realize recovery. The experiments indicate that in cloud and snow weather, the recovery system based on the robot vision can recovery the UAV effectively.
海洋环境下基于机器人视觉的固定翼蜂群回收系统研究
利用机械臂实现无人机的回收在海洋环境中有着广泛的应用;然而,由于海洋环境的复杂性(如云雪天气、高光强),在无人机的回收过程中,基于现有的机器视觉方法无法准确反映机械臂与无人机之间的相对位置关系。本文提出了一种基于双目摄像机aruco码的视觉识别算法来解决上述问题。首先加入中值滤波处理,消除二维码视觉识别过程中的椒盐噪声;然后,采用一种新的二值转换方法获得机器人手臂与无人机之间的精确相对位置。最后,根据机器人的相对位置信息,进行路径规划和控制,实现回收。实验表明,在云雪天气下,基于机器人视觉的无人机回收系统能够有效地对无人机进行回收。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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