Autonomous ROV inspections of aquaculture net pens using DVL

This article presents a method for guiding a remotely operated vehicle (ROV) to autonomously traverse an aquaculture net pen. The method is based on measurements from a Doppler velocity log (DVL) and uses the measured length of the DVL beam vectors to approximate the geometry of a local region of the net pen in front of the ROV. The ROV position and orientation relative to this net pen approximation are used as inputs to a nonlinear guidance law. The guidance law is based upon the line-of-sight (LOS) guidance law. By utilizing that an ROV is fully actuated in the horizontal plane, the crosstrack error is minimized independently of the ROV heading. A Lyapunov analysis of the closed-loop system with this guidance law shows that the ROV is able to follow a continuous path in the presence of a constant irrotational ocean current. Finally, results from simulations and experiments demonstrating the performance of the net pen approximation and control system are presented.acceptedVersio

Robust Nonlinear ROV Motion Control for Autonomous Inspections of Aquaculture Net Pens

Denne oppgaven presenterer en metode for a kontrollere en fjernstyrt undervannsbåt (ROV) til å autonomt traversere og inspisere en not for bruk i fiskeoppdrett. Metoden er basert på Doppler velocity log- (DVL) målinger, og bruker disse målingene til å estimere ROVens posisjon og orientering relativt til nota. Reiseavstanden til de 4 hydroakustiske DVL-strålene er målt, og fra disse fire målingene så er notoverflaten approksimert som et plan. ROVens pekeretning og avstand til den approksimerte notoverflaten blir videre brukt i en guidingslov. Den foreslåtte ulineære guidningsloven er basert på siktlinje-banefølging (LOS), og bruker at ROVen er full-aktuert i det horisontale planet til å styre ROVen mot den ønskede banen uavhengig av ROVens pekeretning. Gjennom Lyapunov-analyse så blir det vist at ROVens distanse til referansebanen konvergerer mot null. For å regulere tilstandene til ROVen, så foreslås både en 1. ordens sliding mode-regulator og en super-twisting algoritme med adaptive pådrag, og gjennom simuleringer er responsen til de foreslåtte regulatorene sammenlignet med klassisk PID-regulatorer. Systemet har blitt designet og tested via simuleringsplattformen FhSim, utviklet av SINTEF Ocean. ROVen presterer bra under simuleringer, og er i stand til å presist følge nota under påvirkning av både bølger og havstrøm. Videre har det blitt gjennomført praktiske eksperimenterer både i basseng, samt på SINTEF ACE, et fullskala fiskeoppdrettslaboratorium. Eksperimentene viser at ROVen er i stand til å autonomt følge nota

Autonomous ROV inspections of aquaculture net pens using DVL

This article presents a method for guiding a remotely operated vehicle (ROV) to autonomously traverse an aquaculture net pen. The method is based on measurements from a Doppler velocity log (DVL) and uses the measured length of the DVL beam vectors to approximate the geometry of a local region of the net pen in front of the ROV. The ROV position and orientation relative to this net pen approximation are used as inputs to a nonlinear guidance law. The guidance law is based upon the line-of-sight (LOS) guidance law. By utilizing that an ROV is fully actuated in the horizontal plane, the crosstrack error is minimized independently of the ROV heading. A Lyapunov analysis of the closed-loop system with this guidance law shows that the ROV is able to follow a continuous path in the presence of a constant irrotational ocean current. Finally, results from simulations and experiments demonstrating the performance of the net pen approximation and control system are presented

Autonomous ROV inspections of aquaculture net pens using DVL

This article presents a method for guiding a remotely operated vehicle (ROV) to autonomously traverse an aquaculture net pen. The method is based on measurements from a Doppler velocity log (DVL) and uses the measured length of the DVL beam vectors to approximate the geometry of a local region of the net pen in front of the ROV. The ROV position and orientation relative to this net pen approximation are used as inputs to a nonlinear guidance law. The guidance law is based upon the line-of-sight (LOS) guidance law. By utilizing that an ROV is fully actuated in the horizontal plane, the crosstrack error is minimized independently of the ROV heading. A Lyapunov analysis of the closed-loop system with this guidance law shows that the ROV is able to follow a continuous path in the presence of a constant irrotational ocean current. Finally, results from simulations and experiments demonstrating the performance of the net pen approximation and control system are presented

Robust adaptive backstepping DP control of ROVs

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.publishedVersio

Robust adaptive backstepping DP control of ROVs

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

ROV Navigation in a Fish Cage with Laser-Camera Triangulation

Aquaculture net cage inspection and maintenance is a central issue in fish farming. Inspection using autonomous underwater vehicles is a promising solution. This paper proposes laser-camera triangulation for pose estimation to enable autonomous net following for an autonomous vehicle. The laser triangulation 3D data is experimentally compared to a doppler velocity log (DVL) in an active fish farm. We show that our system is comparable in performance to a DVL for distance and angular pose measurements. Laser triangulation is promising as a short distance ranging sensor for autonomous vehicles at a low cost compared to acoustic sensors