基准标记
计算机科学
水下
机器人
人工智能
计算机视觉
定位系统
全球定位系统
同步(交流)
实时计算
同时定位和映射
机器人学
信号(编程语言)
移动机器人
探测器
功率(物理)
弹道
衰减
遥控水下航行器
室内定位系统
计算机硬件
搜救
无人机
机器视觉
嵌入式系统
模拟
现场可编程门阵列
无线
遥感
作者
Young-woon Song,Dongsub Kim,Bonchul Ku,Woojin Seol,Son-Cheol Yu
出处
期刊:IEEE Access
[Institute of Electrical and Electronics Engineers]
日期:2026-01-01
卷期号:14: 9139-9156
标识
DOI:10.1109/access.2026.3654109
摘要
Underwater robots face significant positioning challenges, as conventional terrestrial methods like GPS and infrared motion capture fail in underwater environments due to the attenuation of electromagnetic waves. In addition, acoustic-based methods suffer from signal reflections on walls in confined environments. However, centimeter-level positioning accuracy is required to perform precise inspection in environments used in industrial applications such as spent-fuel tanks in nuclear power plants or fire-protection reservoirs. Although fiducial markers offer a potential solution, inconsistent underwater lighting conditions severely reduce how reliably they can be recognized. In this study, we present an active fiducial marker system that addresses these limitations by using LED strobe illumination for reliable and accurate underwater robot positioning. The proposed system features an LED array capable of dynamically generating fiducial marker patterns using blue LEDs at a 475 nm wavelength to minimize water absorption. A vision-based synchronization strategy is integrated to enable coordination between the marker and the camera without external communication, and strobe operation is used to reduce power consumption and motion blur. The marker cell design was optimized by testing its illuminance and uniformity to achieve optimal recognition performance. The results of an experimental evaluation in an industrial water tank demonstrated centimeter-level positioning accuracy (within 2% error) and consistent detection even under extreme lighting conditions where conventional passive markers fail, while also providing vision-based communication capability by changing the marker’s ID. The system enables precise positioning for industrial water tank inspection and research with underwater robots. The proposed approach is well-suited for mobile applications and provides a cost-effective alternative to expensive underwater motion-capture systems while maintaining high positioning accuracy.
科研通智能强力驱动
Strongly Powered by AbleSci AI