Autonomous inspection of a net cage for fish farms using sonar based sensors and sliding mode control techniques for trajectory tracking

Abstract

Inspection operations at fish farms are continuous and time-consuming tasks for operators. This task demands significant effort because it typically relies on divers, who are restricted by their limited underwater time and often exposed to numerous environmental hazards. Utilizing underwater robots has been a strategy to mitigate risks and enhance the safety and comfort of operators at fish farms. This study addresses the net inspection problem by using an underwater robot, sonar-based sensors, and an adaptive sliding mode controller. A simulator developed in Matlab and Simulink, featuring a net cage model and the mathematical modeling of the underwater robot, was used to test the algorithm. This research contributes to the fields of underwater inspection, aquaculture, nonlinear control theory, and trajectory tracking.