A feedback motion strategy applied to a UAV to work as an autonomous relay node for maritime operations

One important aspect that needs to be carefully considered in maritime operations using unmanned robotic vehicles is the communication restrictions between the vehicles and the mission controller that arises mainly due to long distances and/or low power transmissions. This paper addresses the problem of maintaining a communication link between a command station and an Unmanned Aerial Vehicle (UAV) with limited communication range during maritime operations. The proposed scheme uses an additional UAV that acts as a relay for the communication between the command station and the UAV in mission and is actively driven to maintain a desired Quality-of-Service (QoS) level, defined in this paper. Exploiting this architecture, it is possible to plan a maritime operation for a robotic vehicle without the need of considering vehicle-to-command-station communication constraints that will be satisfied by the introduction of the extra autonomous relay-UAVs. To this end, we propose a feedback strategy that has the dual task of commanding and optimizing the execution of the relay UAV motion tasks and adapting the scheduler algorithm according to a desired QoS level. The performance of the proposed strategy is illustrated through computer simulations and preliminary experimental results.

[1]  Paul H. Morris,et al.  Mixed-Initiative Constraint-Based Activity Planning for Mars Exploration Rovers , 2004 .

[2]  Tor Arne Johansen,et al.  UAVs Trajectory Planning by Distributed MPC under Radio Communication Path Loss Constraints , 2015, J. Intell. Robotic Syst..

[3]  Debasish Ghose,et al.  Decentralized Multi-UAV Coalition Formation with Limited Communication Ranges , 2015 .

[4]  Daniel P. Raymer,et al.  Aircraft Design: A Conceptual Approach , 1989 .

[5]  J. R. Martinez-de Dios,et al.  Cooperation Between UAS and Wireless Sensor Networks for Efficient Data Collection in Large Environments , 2013, J. Intell. Robotic Syst..

[6]  J. Aiken,et al.  REMOTE SENSING OF OCEANIC BIOLOGY IN RELATION TO GLOBAL CLIMATE CHANGE , 1992 .

[7]  Tor Arne Johansen,et al.  Path Planning for UAVs Under Communication Constraints Using SPLAT! and MILP , 2012, J. Intell. Robotic Syst..

[8]  Álvaro Marco,et al.  Unmanned Aerial Vehicle Based Wireless Sensor Network for Marine-Coastal Environment Monitoring , 2017, Sensors.

[9]  Asgeir J. Sørensen,et al.  Unmanned aerial vehicle as communication relay for autonomous underwater vehicle — Field tests , 2014, 2014 IEEE Globecom Workshops (GC Wkshps).

[10]  A. Pedro Aguiar,et al.  VirtualArena: An object-oriented MATLAB toolkit for control system design and simulation , 2017, 2017 International Conference on Unmanned Aircraft Systems (ICUAS).

[11]  Juliane Hahn Radio Electronic Transmission Fundamentals , 2016 .

[12]  Sang Hyuk Son,et al.  Feedback Control Real-Time Scheduling: Framework, Modeling, and Algorithms* , 2001, Real-Time Systems.

[13]  R. S. Ponmagal,et al.  Link Quality Estimated TCP for Wireless Sensor Networks , 2009 .

[14]  J. Gaspar,et al.  CONTROL OF UNICYCLE TYPE ROBOTS Tracking, Path Following and Point Stabilization , 2008 .

[15]  Ricardo Martins Disruption/delay tolerant networking with low-bandwidth underwater acoustic modems , 2010, 2010 IEEE/OES Autonomous Underwater Vehicles.

[16]  Anibal Ollero,et al.  Area decomposition, partition and coverage with multiple remotely piloted aircraft systems operating in coastal regions , 2016, 2016 International Conference on Unmanned Aircraft Systems (ICUAS).

[17]  Seppo J. Ovaska,et al.  Real-Time Systems Design and Analysis: Tools for the Practitioner , 2011 .