Control System Architecture for Automatic Recovery of Fixed-Wing Unmanned Aerial Vehicles in a Moving Arrest System

Automatic recovery is an important step in enabling fully autonomous missions using fixed-wing unmanned aerial vehicles (UAVs) operating from ships or other moving platforms. However, automatic recovery in moving arrest systems is only briefly studied in the research literature, and is not yet an option when using low-cost, commercial off-the-shelf (COTS) autopilots. Acknowledging the reliability and low cost of COTS avionics, this paper adds recovery functionality as a modular extension based on non-intrusive additions to an autopilot with very general assumptions on its interface. This is achieved by line-of-sight guidance, which sends an augmented desired position to the autopilot, to ensure line-following along a virtual runway that guides the UAV into the arrest system. The translation and rotation of this line is determined by the pose of the arrest system, determined using two Global Navigation Satellite System (GNSS) receivers, where one is configured as a Real-Time Kinematic (RTK) base station. The relative position of the UAV and arrest system is also precisely estimated using RTK GNSS. Through extensive field testing, on two different fixed-wing UAVs, the system has shown its performance and reliability; 43 recovery attempts in a stationary net hit 0.01 ± 0.25m to the right and 0.07 ± 0.20m below the target in calm conditions. Further, 15 recoveries in a barge-mounted, ship-towed net hit 0.06 ± 0.53m to the right and 0.98 ± 0.27m below the target in winds up to 4 m/s. The remaining error is largely systematic, caused by communication delays, and could be reduced with more integral effect or through direct compensation.

[1]  L. Dubins On Curves of Minimal Length with a Constraint on Average Curvature, and with Prescribed Initial and Terminal Positions and Tangents , 1957 .

[2]  Yue Meng,et al.  A visual/inertial integrated landing guidance method for UAV landing on the ship , 2019, Aerospace Science and Technology.

[3]  Tor Arne Johansen,et al.  User-Configurable Timing and Navigation for UAVs , 2018, Sensors.

[4]  Sergey Khantsis,et al.  UAV Controller Design Using Evolutionary Algorithms , 2005, Australian Conference on Artificial Intelligence.

[5]  David Hyunchul Shim,et al.  A Vision-Based Automatic Landing Method for Fixed-Wing UAVs , 2010, J. Intell. Robotic Syst..

[6]  Gui-Song Xia,et al.  A survey on vision-based UAV navigation , 2018, Geo spatial Inf. Sci..

[7]  Christos Papachristos,et al.  Keyframe‐based thermal–inertial odometry , 2019, J. Field Robotics.

[8]  Xiang Zhou,et al.  Airborne Vision-Based Navigation Method for UAV Accuracy Landing Using Infrared Lamps , 2013, J. Intell. Robotic Syst..

[9]  Youdan Kim,et al.  Spiral Landing Trajectory and Pursuit Guidance Law Design for Vision-Based Net-Recovery UAV , 2009 .

[10]  Konstantin Kondak,et al.  A Novel Landing System to Increase Payload Capacity and Operational Availability of High Altitude Long Endurance UAVs , 2016, 2016 International Conference on Unmanned Aircraft Systems (ICUAS).

[11]  Tor Arne Johansen,et al.  Wave motion compensation in dynamic positioning of small autonomous vessels , 2020, Journal of Marine Science and Technology.

[12]  Robin R. Murphy,et al.  CONOPS and autonomy recommendations for VTOL small unmanned aerial system based on Hurricane Katrina operations , 2009, J. Field Robotics.

[13]  Kristoffer Gryte,et al.  Robust Navigation of UAV using Inertial Sensors Aided by UWB and RTK GPS , 2017 .

[14]  Kristin Ytterstad Pettersen,et al.  On uniform semiglobal exponential stability (USGES) of proportional line-of-sight guidance laws , 2014, Autom..

[15]  Tor Arne Johansen,et al.  Autonomous recovery of a fixed‐wing UAV using a net suspended by two multirotor UAVs , 2018, J. Field Robotics.

[16]  David Hyunchul Shim,et al.  A Guidance and Control Law Design for Precision Automatic Take-off and Landing of Fixed-Wing UAVs , 2012 .

[17]  Todd E. Humphreys,et al.  Unmanned Aircraft Capture and Control Via GPS Spoofing , 2014, J. Field Robotics.

[18]  Hriday Bavle,et al.  A Deep Reinforcement Learning Strategy for UAV Autonomous Landing on a Moving Platform , 2018, Journal of Intelligent & Robotic Systems.

[19]  Matthew J. Rutherford,et al.  A Survey of Controller Designs for New Generation UAVs: The Challenge of Uncertain Aerodynamic Parameters , 2020 .

[20]  Thor I. Fossen,et al.  Handbook of Marine Craft Hydrodynamics and Motion Control: Fossen/Handbook of Marine Craft Hydrodynamics and Motion Control , 2011 .

[21]  Pascual Campoy Cervera,et al.  An Approach Toward Visual Autonomous Ship Board Landing of a VTOL UAV , 2014, 2013 International Conference on Unmanned Aircraft Systems (ICUAS).

[22]  Michael Knight,et al.  A Biologically Inspired, Vision‐based Guidance System for Automatic Landing of a Fixed‐wing Aircraft , 2014, J. Field Robotics.

[23]  Rishad A. Irani,et al.  Methodologies for landing autonomous aerial vehicles on maritime vessels , 2020 .