This paper provides a systematic state of the art review on tracking the fine scale movements of fish with the use of autonomous maritime robotics. Knowledge of migration patterns and the localization of specific species of fish at a given time is vital to many aspects of conservation. This paper reviews these technologies and provides insight into what systems are being used and why. The review results show that a larger amount of complex systems that use a deep learning techniques are used over more simplistic approaches to the design. Most results found in the study involve Autonomous Underwater Vehicles, which generally require the most complex array of sensors. The results also provide insight into future research such as methods involving swarm intelligence, which has seen an increase in use in recent years. This synthesis of current and future research will be helpful to research teams working to create an autonomous vehicle with intentions to track, navigate or survey.

本文提供了使用自动海上机器人技术跟踪鱼的细小尺度运动的系统的最新技术回顾。在给定时间内了解迁移模式和特定鱼类的本地化对于保护的许多方面至关重要。本文回顾了这些技术，并深入了解了正在使用的系统以及原因。审查结果显示，使用大量使用深度学习技术的复杂系统，而不是采用更简单的设计方法。研究中发现的大多数结果都涉及自动水下航行器，这通常需要最复杂的传感器阵列。这些结果还提供了对未来研究的洞察力，例如涉及群智能的方法，近年来这种方法的使用有所增加。