Dynamic positioning is an important control feature for an underwater remotely operated vehicle. This paper presents a nonlinear dynamic positioning controller suited for application to vehicles with model uncertainties, operating in environments with unpredictable disturbances, such as an aquaculture net cage. The proposed controller combines the backstepping approach with an adaptation term to ensure robustness. Using Lyapunov theory and Matrosov’s theorem the origin of the closed-loop system is proven to be: (i) globally asymptotically stable when assuming persistency of excitation, and (ii) stable and bounded, with the true position converging to the desired position if there is no persistency of excitation. This paper also presents results from simulations where the proposed controller is contextualized and compared to similar controllers, showing promising results. Finally, as the main result of the manuscript that demonstrates the effectiveness of the proposed control law, an extensive field trial campaign is conducted at a full-scale aquaculture site using an industrial ROV where the proposed controller is successfully tested under realistic operational conditions.