随着无人机和无人艇技术的迅速发展，无人机-无人艇协同应用逐渐成为未来海上军事任务和智慧交通的不可或缺组成部分。然而，考虑到无人艇在不同海况条件下的高动态特性，传统的雷达等手段虽然可以满足高精度和实时性的要求，但成本较高，而传统的视觉方法虽然成本低、易于实现，但稳定度较低。本文基于相机成像原理，提出一种无人机与无人艇的单目定距方法。通过对着陆区域的多个标志物进行识别定距后，对无人艇着陆区域平面进行拟合重构，从而获取无人机与无人艇的距离，标志物越多，算法失效的概率越低。搭建数值模拟器对算法进行了测试，研究了算法在无人艇大倾角摇晃下的精度和稳定性。结果显示，算法在无人艇摇晃的情况下可以得到较为准确的距离，所有工况计算出X，Y，Z方向上的平均相对误差分别为7.47%、6.48%和8.04%。
With the rapid advancement of unmanned drone and vessel technologies, the collaborative application of unmanned drones and vessel is gradually becoming an indispensable component of future maritime military missions and smart transportation. However, considering the high dynamic characteristics of unmanned vessels under different sea conditions, traditional methods such as radar, while meeting the requirements for high accuracy and real-time performance, incur high costs. On the other hand, traditional vision-based approaches, though cost-effective and easy to implement, suffer from lower stability. This paper proposes a monocular method for unmanned drone and vessel system based on the principles of pinhole camera model. By identifying and ranging multiple landmarks in the landing area, a plane fitting reconstruction of the landing area for the unmanned vessel is performed, enabling the determination of the distance between the unmanned drone and vessel. The more landmarks identified, the lower the probability of algorithm failure. A numerical simulator was constructed to test the algorithm, evaluating its accuracy and stability under the large-angle rotation of the unmanned vessel. The results demonstrate that the algorithm can obtain accurate distances, with average relative errors in the X, Y and Z directions of 7.47%, 6.48% and 8.04%, respectively.
2024,46(16): 81-89 收稿日期：2023-09-25
DOI：10.3404/j.issn.1672-7649.2024.16.014
分类号：U664.82
基金项目：海南省自然科学基金资助项目（521QN275）；国家自然科学基金资助项目（42206192，52031006）
作者简介：邓涛（1997 – ），男，硕士研究生，研究方向为智能船舶
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