Collecting Information for Biomass Estimation in Mariculture with a Heterogeneous Robotic System

Abstract

In this paper, we address the problem of fish stock estimation in marine fisheries using a heterogeneous robotic system consisting of unmanned aerial vehicles (UAVs) and unmanned underwater vehicles (UUVs). UAVs take aerial photographs of the cage during fish feeding, while UUVs take photographs of fish from top to bottom in the cage. The photos and videos obtained provide the input data for estimating the number of fish and the amount of biomass of fish in the cage. The paper analyzes a number of factors that affect the accuracy of the estimate. Preliminary results obtained with an approximate method for estimating the number of fish, based on the processing of images obtained in a virtual simulator and resembling aerial photographs of fish taken during feeding, are described. The results obtained show that this problem is extremely complex and that it is worth trying to use machine learning and artificial intelligence methods to achieve the desired maximum estimation error of less than 20%.