基于单目视觉的微型无人机目标跟踪算法研究

J. Robotics Pub Date : 2023-07-04 DOI:10.1155/2023/6657120
Yingbin Feng, Dian Wang, Kun Yang
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引用次数: 0

摘要

针对微型无人机载荷和续航能力有限的问题,提出了基于单目视觉的目标跟踪算法。由于单目视觉无法直接测量无人机与目标之间的距离,因此采用三角测量和三角相似度来计算距离信息。然后,设计了一种基于卡尔曼滤波和KCF的目标跟踪方法。利用卡尔曼滤波对KCF的跟踪结果进行修正,解决了目标遮挡问题。最后,通过坐标变换矩阵计算目标在世界坐标系中的位置,用于控制无人机跟踪运动目标。为了验证算法的可行性,进行了目标尺寸估计和目标跟踪算法。实验结果表明,该算法能在短时遮挡条件下对运动目标进行有效跟踪。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Target Tracking Algorithm of Micro-UAV Based on Monocular Vision
Aiming at the problem of limited payload and endurance of micro-UAV, the target tracking algorithm based on monocular vision is proposed. Since monocular vision cannot directly measure distance between the UAV and the target, triangulation and triangle similarity are used to calculate the distance information. Then, a target tracking method based on Kalman filter and KCF is designed. The tracking result of KCF is modified by Kalman filter to solve the problem of target occlusion. Finally, the position of the target in the world coordinate system is calculated through the coordinate transformation matrix, which is used to control the UAV for tracking the moving target. In order to verify the feasibility of the algorithm, target size estimation and target tracking algorithms are carried out. The experimental results show that the proposed algorithm can track the moving target effectively under the condition of short-term occlusion.
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