Tracking the fine scale movements of fish using autonomous maritime robotics: A systematic state of the art review

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.

Automated summary

This paper provides a comprehensive review of using autonomous maritime robotics to track the fine scale movements of fish, showing a trend towards more complex systems and deep learning techniques. The results mainly focus on Autonomous Underwater Vehicles and suggest potential future research directions involving swarm intelligence methods.