Laplacian regularized motion tomography for underwater vehicle flow mapping with sporadic localization measurements

IF 3.7 3区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Autonomous Robots Pub Date : 2024-05-24 DOI:10.1007/s10514-024-10165-5

Ouerghi Meriam, Hou Mengxue, Zhang Fumin

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Abstract

Localization measurements for an autonomous underwater vehicle (AUV) are often difficult to obtain. In many cases, localization measurements are only available sporadically after the AUV comes to the sea surface. Since the motion of AUVs is often affected by unknown underwater flow fields, the sporadic localization measurements carry information of the underwater flow field. Motion tomography (MT) algorithms have been developed to compute a underwater flow map based on the sporadic localization measurements. This paper extends MT by introducing Laplacian regularization in to the problem formulation and the MT algorithm. Laplacian regularization enforces smoothness in the spatial distribution of the underwater flow field. The resulted Laplacian regularized motion tomography (RMT) algorithm converges to achieve a finite error bounded. The performance of the RMT and other variants of MT are compared through the method of data resolution analysis. The improved performance of RMT is confirmed by experimental data collected from underwater glider ocean sensing experiments.

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利用零星定位测量绘制水下航行器流动图的拉普拉斯正则化运动断层成像技术

自动潜航器（AUV）的定位测量通常很难获得。在许多情况下，只有在 AUV 到达海面后才能获得零星的定位测量数据。由于自动潜航器的运动通常会受到未知水下流场的影响，因此零星的定位测量会携带水下流场的信息。目前已开发出基于零星定位测量值计算水下流场图的运动层析（MT）算法。本文在问题表述和 MT 算法中引入了拉普拉斯正则化，对 MT 进行了扩展。拉普拉斯正则化能使水下流场的空间分布更加平滑。由此产生的拉普拉斯正则化运动断层扫描（RMT）算法收敛后达到有限误差约束。通过数据分辨率分析方法，比较了 RMT 和其他 MT 变体的性能。水下滑翔机海洋传感实验收集的数据证实了 RMT 性能的提高。

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来源期刊

Autonomous Robots 工程技术-机器人学

CiteScore

7.90

自引率

5.70%

发文量

审稿时长

3 months

期刊介绍： Autonomous Robots reports on the theory and applications of robotic systems capable of some degree of self-sufficiency. It features papers that include performance data on actual robots in the real world. Coverage includes: control of autonomous robots · real-time vision · autonomous wheeled and tracked vehicles · legged vehicles · computational architectures for autonomous systems · distributed architectures for learning, control and adaptation · studies of autonomous robot systems · sensor fusion · theory of autonomous systems · terrain mapping and recognition · self-calibration and self-repair for robots · self-reproducing intelligent structures · genetic algorithms as models for robot development. The focus is on the ability to move and be self-sufficient, not on whether the system is an imitation of biology. Of course, biological models for robotic systems are of major interest to the journal since living systems are prototypes for autonomous behavior.