Cooperative visual positioning method of multiple unmanned surface vehicles in subterranean closed water body

doi:10.11772/j.issn.1001-9081.2023121827

Journal of Computer Applications ›› 2025, Vol. 45 ›› Issue (1): 325-336.DOI: 10.11772/j.issn.1001-9081.2023121827

• Frontier and comprehensive applications • Previous Articles Next Articles

Cooperative visual positioning method of multiple unmanned surface vehicles in subterranean closed water body

Wenbo CHE¹, Jianhua WANG¹(), Xiang ZHENG¹, Gongxing WU¹, Shun ZHANG², Haozhu WANG¹

^1.Key Laboratory of Transport Industry of Marine Technology and Control Engineering，Ministry of Transport （Shanghai Maritime University），Shanghai 201306，China
^2.Shanghai AutoSubsea Vehicles Incorporated，Shanghai 201306，China

Received:2024-01-02 Revised:2024-04-02 Accepted:2024-04-07 Online:2024-04-19 Published:2025-01-10
Contact: Jianhua WANG
About author:CHE Wenbo， born in 1999， M. S. candidate. His research interests include control of unmanned surface vehicle， visual detection positioning and navigation.
ZHENG Xiang， born in 1981， Ph. D.， lecturer. Her research interests include motion control of unmanned surface vehicle， intelligent structure seismic control.
WU Gongxing， born in 1983， Ph. D.， associate professor. His research interests include ship handling and control.
ZHANG Shun， born in 1990， M. S.， engineer. His research interests include marine engineering， underwater robot.
WANG Haozhu， born in 1997， M. S. candidate. His research interests include perceptual decision-making and control of unmanned surface vehicle based on LiDAR.
Supported by:
National Natural Science Foundation of China(52271322)

地下封闭水体内多无人艇协同的视觉定位方法

车文博¹, 王建华¹(), 郑翔¹, 吴恭兴¹, 张舜², 王浩铸¹

^1.航运技术与控制工程交通运输行业重点实验室（上海海事大学），上海 201306
^2.上海遨拓深水装备技术开发有限公司，上海 201306

通讯作者: 王建华
作者简介:车文博（1999—），男，山东威海人，硕士研究生，主要研究方向：无人水面艇控制、视觉检测定位与导航；
郑翔（1981—），女，江苏扬州人，讲师，博士，主要研究方向：无人艇运动控制、智能结构减震控制；
吴恭兴（1983—），男，江西抚州人，副教授，博士，主要研究方向：船舶操纵与控制；
张舜（1990—），男，安徽亳州人，工程师，硕士，主要研究方向：海洋工程、水下机器人；
王浩铸（1997—），男，山东临沂人，硕士研究生，主要研究方向：激光雷达的无人艇感知决策与控制。
基金资助:
国家自然科学基金资助项目(52271322)

Abstract

Abstract:

Aiming at the problems of lack of satellite positioning signal， limited communication and weak ambient light of Unmanned Surface Vehicle （USV） in subterranean closed water body， a cooperative visual positioning method of multiple USVs in subterranean closed water body was proposed. Firstly， a vehicle-borne light source cooperative marker was designed， and the marker structure was optimized according to the vehicle structure and application scene. Secondly， monocular vision was used to collect the marker images， and the image coordinates of the feature points were solved. Thirdly， on the basis of camera imaging model， by using the relationship between the spatial coordinates of feature points of the markers and the corresponding image coordinates， the relative positions between adjacent vehicles were calculated through improving direct linear transformation method. Fourthly， the cameras of the front and rear vehicles were used to make look face to face between the vehicles. Through the minimum variance algorithm， the relative positions calculated on the basis of the camera images of the front and rear vehicles were fused to improve the relative positioning accuracy. Finally， the absolute location of each USV was obtained by using the known absolute coordinates in the scene. The factors influencing positioning error were analyzed through simulation， and the proposed method was compared with the traditional direct linear transformation method. The results show that as the distance increases， the effect of this method becomes more obvious. At a distance of 15 m， the position variance solved by the proposed method is stable within 0.2 m²， verifying the accuracy of this method. Static experimental results show that the proposed method can stabilize the relative error within 10.0%； dynamic experimental results in underground river courses show that the absolute positioning navigation trajectory solved by the proposed method achieves accuracy similar to satellite positioning， which verifies the feasibility of this method.

Key words: Unmanned Surface Vehicle (USV), cooperative positioning, monocular vision, cooperative marker, subterranean closed water body

摘要：

针对无人艇（USV）在地下封闭水体中卫星定位信号缺失、通信受限、环境光线弱等问题，提出一种地下封闭水体内多USV协同的视觉定位方法。首先，设计一种艇载光源合作标志物，并根据艇身结构与应用场景对标志物结构进行优化；其次，采用单目视觉采集标志物图像，并求取特征点的图像坐标；再次，根据摄像机成像模型，基于合作标志物特征点的空间坐标及其对应的图像坐标之间的关系，通过改进直接线性变换方法求解相邻艇间的相对位置；然后，利用前后艇的摄像机进行艇间对视，并通过最小方差算法，融合根据前后艇摄像机图像求解所得的相对位置，以提高相对定位精度；最后，利用场景中已知的绝对坐标，获得各无人艇的绝对位置。仿真实验对影响定位误差的因素进行分析，并把所提方法与传统直接线性变换方法进行对比。结果表明，随着距离的增加，所提方法求解优势更趋明显，在距离15 m时求解的位置方差稳定在0.2 m²以内，验证了所提方法的准确性。静态实验结果表明，所提方法能将相对误差稳定在10.0%以内；地下河道内的动态实验结果表明，所提方法求解的绝对定位的航行轨迹达到与卫星定位相当的精度，验证了所提方法的可行性。

关键词: 水面无人艇, 协同定位, 单目视觉, 合作标志物, 地下封闭水体

CLC Number:

TP212.9

Wenbo CHE, Jianhua WANG, Xiang ZHENG, Gongxing WU, Shun ZHANG, Haozhu WANG. Cooperative visual positioning method of multiple unmanned surface vehicles in subterranean closed water body[J]. Journal of Computer Applications, 2025, 45(1): 325-336.

车文博, 王建华, 郑翔, 吴恭兴, 张舜, 王浩铸. 地下封闭水体内多无人艇协同的视觉定位方法[J]. 《计算机应用》唯一官方网站, 2025, 45(1): 325-336.

Figures/Tables 17

Fig. 1 Application scene

Fig. 2 Schematic diagram of cooperative visual positioning of multiple USVs

Fig. 3 Cooperative marker structures

Fig. 4 Cooperative marker projection process

Fig. 5 Design of cooperative markers

Fig. 6 Image processing flow

Fig. 7 Relative positions solved with unoptimized cooperative markers

Tab. 1 Optimization of marker structure parameters

序号	N	L_z1/m	L_z2/m	L_z3/m	$(σ i f) 2$ /m²
1	6	0.10	0.25		20.00
2	6	0.15	0.20		6.00
3	6	0.10	0.30		15.00
4	6	0.15	0.25		10.00
5	8	0.10	0.25	0.60	0.60
6	8	0.10	0.20	0.45	0.80
7	8	0.10	0.40	0.20	0.40
8	8	0.08	0.22	0.55	0.20
9	8	0.05	0.20	0.50	0.50
10	8	0.10	0.25	0.25	4.00

Tab. 1 Optimization of marker structure parameters

序号	N	L_z1/m	L_z2/m	L_z3/m	$(σ i f) 2$ /m²
1	6	0.10	0.25		20.00
2	6	0.15	0.20		6.00
3	6	0.10	0.30		15.00
4	6	0.15	0.25		10.00
5	8	0.10	0.25	0.60	0.60
6	8	0.10	0.20	0.45	0.80
7	8	0.10	0.40	0.20	0.40
8	8	0.08	0.22	0.55	0.20
9	8	0.05	0.20	0.50	0.50
10	8	0.10	0.25	0.25	4.00

Fig. 8 Relative positions solved with optimized cooperative markers

Fig. 9 Relative position errors under influence of rotations

Fig. 10 Analysis of data fusion effect

Fig. 11 Absolute positioning trajectory

Fig. 12 Box plot of relative position results

Tab. 2 Solution results of static experiments

位置序号	均值/m			方差/m²			相对误差/%
位置序号	$t U S V 1 b$ （3）	$t U S V 1 f$ （3）	$t f u s 1 (3)$	$σ U S V 1 2$	$σ U S V 2 2$	$σ f u s 1 2$	相对误差/%
1	6.65	6.54	6.61	0.02	0.03	0.01	1.6
2	8.03	7.84	7.95	0.06	0.07	0.03	2.1
3	9.42	9.14	9.30	0.21	0.26	0.11	3.5
4	10.20	11.44	10.59	0.25	0.55	0.18	4.0
5	10.97	13.75	11.73	0.72	1.93	0.50	6.0
6	11.77	15.10	12.48	0.72	2.62	0.55	5.9
7	12.55	16.46	13.13	1.77	10.32	1.56	9.5
8	13.44	17.33	14.43	1.82	5.29	1.51	8.5

Tab. 2 Solution results of static experiments

位置序号	均值/m			方差/m²			相对误差/%
位置序号	$t U S V 1 b$ （3）	$t U S V 1 f$ （3）	$t f u s 1 (3)$	$σ U S V 1 2$	$σ U S V 2 2$	$σ f u s 1 2$	相对误差/%
1	6.65	6.54	6.61	0.02	0.03	0.01	1.6
2	8.03	7.84	7.95	0.06	0.07	0.03	2.1
3	9.42	9.14	9.30	0.21	0.26	0.11	3.5
4	10.20	11.44	10.59	0.25	0.55	0.18	4.0
5	10.97	13.75	11.73	0.72	1.93	0.50	6.0
6	11.77	15.10	12.48	0.72	2.62	0.55	5.9
7	12.55	16.46	13.13	1.77	10.32	1.56	9.5
8	13.44	17.33	14.43	1.82	5.29	1.51	8.5

Fig. 13 Experimental scene

Fig. 14 Relative positions between vehicles

Fig. 15 Absolute positioning trajectories of USV1 and USV2

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Cooperative visual positioning method of multiple unmanned surface vehicles in subterranean closed water body

地下封闭水体内多无人艇协同的视觉定位方法

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