Methodologies for landing autonomous aerial vehicles on maritime vessels
Aerospace Science and Technology , Volume 106
One of the key challenges to the safe operation of UAVs at sea is the relative motion that exists between the UAV and ship during landing. The scope of this work is the development and evaluation of methodologies for improving UAV landing performance. The new methodologies are known as the Signal Prediction Algorithm (SPA), Active Heave Compensation (AHC) and the Landing Period Indicator (LPI). To promote interoperability, the methodologies do not require any specific ship equipment. To evaluate the methodologies on an existing comprehensive UAV model, ShipMo3D was used to generate 105 sets of ship motion in sea states 2–6, headings 0–180∘ and speeds 6–10 knots. Within the simulation the UAV, equipped with a Light Detection and Ranging (LIDAR) system, measures the ship motion in situ. Using the Signal Prediction Algorithm (SPA), the UAV forecasts the ship motion and potential landing opportunities. The UAV can also use the SPA and the AHC system to maintain a safe hover position above the ship deck and determine landing trajectories with a specific touchdown velocity. The UAV can also employ the novel Landing Period Indicator (LPI) system which calculates an estimate of the ship's energy and determines opportune times for safe landings. The results indicate that the methodologies can improve the landing performance of autonomous helicopters. For the 105 sets of ship motion, using the combination of the SPA, AHC, and LPI improved landing success by up to 34% when compared to a common landing controller.
|Aircraft landing systems, Autonomous systems, Interoperability, Landing period indicator, Maritime operations, UAV|
|Aerospace Science and Technology|
|Organisation||Department of Mechanical and Aerospace Engineering|
Abujoub, S. (Shadi), McPhee, J. (Johanna), & Irani, R. (2020). Methodologies for landing autonomous aerial vehicles on maritime vessels. Aerospace Science and Technology, 106. doi:10.1016/j.ast.2020.106169