Unmanned Aerial Vehicle Landing on Maritime Vessels using Signal Prediction of the Ship Motion

Abujoub, Shadi; McPhee, Johanna; Westin, Cassidy; Irani, Rishad A.

doi:10.1109/oceans.2018.8604820

Cited by 16 publications

(14 citation statements)

References 10 publications

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“…This chapter is based on a paper that was presented at the Canadian Society for Mechanical Engineering International Congress 2018 (CSME 2018) [37]. Additionally the work was used as part of an unmanned aerial vehicle landing study which was presented at the IEEE Oceans 18 conference [38].…”

Section: Chapter 4 Advancing a Wave Prediction Algorithm For Breach Cmentioning

confidence: 99%

“…Abujoub et al[38] performed a study on unmanned aerial vehicle landings on maritime vessels that used simulated laser ranging and detecting devices(LIDAR) in conjunction with the signal prediction algorithm (SPA) presented in this chapter to forecast when a vessel's motion was within safe landing limits. Their results showed that with the use of the SPA, the number of UAV landing attempts was decreased by an average of 2 attempts, per test case, when compared to a system that did not use an SPA.…”

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confidence: 99%

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Control, Simulation, and Testbed Development for Improving Maritime Launch and Recovery Operations

McPhee¹

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Improvements to launch and recovery operations at sea are driven by the desire to increase safety and operational availability. This thesis presents various tools to improve motion compensation strategies in maritime launch and recovery: a 3D computer simulator to examine wave synchronization, a signal prediction algorithm for Go-NoGo states and a hardware setup to simulate ship and wave motion. The 3D simulator of towed body dynamics was advanced to model the wave interactions with the cable and towed body as the body exits the water. Small scale simulations were run to investigate the inclusion of wave synchronization in established active heave compensation strategies where the hypothesis that wave synchronization would reduce variations in cable tension was not supported; the simulations demonstrated that wave synchronization increased variations in cable tension compared to simulations not using motion compensation. The use of a signal prediction method that forecasts a periodic signal based only on historic data of the signal was explored. The method is a means to predict safe breach events where the prediction algorithm was advanced and tuned to determine Go-NoGo states. A Go scenario identified by the mean and one standard deviation of the predicted signal was found to produce a Go-NoGo signal that agreed most with the desired Go-NoGo signal for forecasts up to 10 s. For the development of laboratory equipment for the Carleton University flume tank, a ship motion simulator was designed and built to emulate 5 degrees-of-freedom of ship motion and a kinematic analysis was performed to characterize the system workspace. For producing waves in the flume tank, a design methodology was developed for the design of a plunger-type wavemaker. A numerical model for determining the wave amplitude to actuator stroke length ratio was advanced to include the effects of a flow current. The design methodology enables the designer to select an appropriate actuator and plunger shape based on an operating point that incorporates multiple design variables.

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Section: Chapter 4 Advancing a Wave Prediction Algorithm For Breach Cmentioning

confidence: 99%

mentioning

confidence: 99%

Control, Simulation, and Testbed Development for Improving Maritime Launch and Recovery Operations

McPhee¹

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“…The following section contains excerpts from a research paper published in proceedings of IEEE Oceans 18 Charleston titled Unmanned Aerial Vehicle Landing on Maritime Vessels using Signal Prediction of the Ship Motion [9]. Figure 3.27 illustrates the notation used in the following section to derive the output of each LIDAR.…”

Section: Lidar Emulationmentioning

confidence: 99%

“…Signal prediction independent of vessel type is currently used for Active Heave Compensation (AHC) on ships utilizing towing winches, allowing the system to actively pay-out or reel-in line to the towed object to attenuate the transmission of the ship's motion to the submerged equipment [7]. It is hypothesized that the same Signal Prediction Algorithm (SPA) used by Woodacre [7] and improved upon by McPhee [8,9] may be used on-board a UAV to facilitate landing. The second outcome of this thesis is the methodology for landing the UAV on a dynamic platform using the same signal prediction algorithm previously improved upon by McPhee.…”

Section: Chapter 1 Introductionmentioning

confidence: 99%

“…The formulation of a landing period indicator to improve UAV landing performance without the use of signal prediction 3. A portion of this research has been presented and published in the proceedings of the IEEE Oceans 18 Conference [9] There are six chapters in this thesis. Chapter 2 reviews existing literature pertaining to helicopter-ship operations, including: wave modelling, ship motion prediction, current landing technology, the UAV platform used in this thesis, and simulation modelling methods.…”

Section: Chapter 1 Introductionmentioning

confidence: 99%

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Development of a Landing Period Indicator and the Use of Signal Prediction to Improve Landing Methodologies of Autonomous Unmanned Aerial Vehicles on Maritime Vessels

Abujoub¹

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Unmanned aerial vehicles (UAVs) are becoming more prevalent in maritime operations. One of the key challenges to the safe operation of UAVs at sea is the relative motion that exists between the UAV and ship. The scope of this thesis is the creation and evaluation of a methodology for improving the overall landing performance for UAVs using signal prediction and a developed Landing Period Indicator (LPI). The research is conducted in a synthetic environment, where the test vehicle is a quad rotor UAV that is equipped with a Light Detection and Ranging (LIDAR) system to aerially detect ship motion. The observed ship motion is forecasted using signal prediction which identifies and notifies the UAV of potential landing opportunities.The Signal Prediction Algorithm (SPA) is also used for Active Heave Compensation (AHC) to facilitate the UAV in maintaining a safe low hover position above the ship deck. Further, an algorithm is developed to use the AHC system to plan trajectories that land the UAV with a specified impact velocity. The development of the LPI system is presented and its performance as a standalone and supplemental system is evaluated. ShipMo3D was used to generate 105 sets of ship motion in sea states 2-6. The results in this thesis indicate that the developed landing methodologies can improve the landing performance of ocean going helicopters. For the 105 sets of ship motion, using a combination of the SPA, AHC, and the LPI improved landing performance by 25% in two separate test groups. Moreover, the results indicate that with further tuning of the SPA, the likelihood of a safe landing can be further improved.

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Experimental tests of hybrid VTOL unmanned aerial vehicle designed for surveillance missions and operations in maritime conditions from ship‐based helipads

Ambroziak

Ciężkowski

Wolniakowski

et al. 2021

Journal of Field Robotics

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This article presents research on a hybrid vertical take‐off and landing (VTOL) unmanned aerial vehicle (UAV) supported by a relative positioning system, enabling the deployment of autonomous missions from ship‐based helipads in maritime conditions. A crucial issue to be solved is ensuring precise positioning of the UAV relative to the landing pad in the take‐off and landing phases. To achieve this, an extended Kalman filter (EKF) is implemented on the UAV's onboard computer, which integrates the positioning data from the UAV's global navigation satellite system receiver and the positioning data of the landing pad broadcast by the landing pad navigation station (LNS). The EKF estimates both the absolute and relative position of the UAV, which are required for autonomous take‐off and landing on the moving landing pad. In unfavorable weather conditions, EKF also uses data from an optional local positioning system to keep the accuracy within the range 1–3 m. The research was concluded by experimental verification during a ferry cruise over the Baltic Sea. During the research, the VTOL UAV performed two fully autonomous flight missions at the range about 1 km from the moving ferry in international waters. Each of them ended with a successful landing back on the helipad with an accuracy matching its required level, which was already achieved in the previous research carried out in inland conditions. Data recorded during real flights confirm that the developed system, consisting of a hybrid VTOL UAV and a LNS, is ready to be utilized in autonomous missions at sea. Factors having a critical impact on the safety of use of the VTOL UAV in marine conditions were also identified, which were not observed during the research in inland conditions, and are related directly to turbulence around the landing pad.

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Unmanned Aerial Vehicle Landing on Maritime Vessels using Signal Prediction of the Ship Motion

Cited by 16 publications

References 10 publications

Control, Simulation, and Testbed Development for Improving Maritime Launch and Recovery Operations

Control, Simulation, and Testbed Development for Improving Maritime Launch and Recovery Operations

Development of a Landing Period Indicator and the Use of Signal Prediction to Improve Landing Methodologies of Autonomous Unmanned Aerial Vehicles on Maritime Vessels

Experimental tests of hybrid VTOL unmanned aerial vehicle designed for surveillance missions and operations in maritime conditions from ship‐based helipads

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