A Review and Future Directions of UAV Swarm Communication Architectures

The utility of unmanned aerial vehicles (UAVs) has significantly disrupted aviation-related industries. As technology and policy continue to develop, this disruption is likely to continue and become even larger in magnitude. A specific technology poised to disrupt industry is UAV swarm. UAV swarm has the potential to distribute tasks and coordinate operation of many drones with little to no operator intervention. This paper surveys literature regarding UAV swarm and proposes a swarm architecture that will allow for higher levels of swarm autonomy and reliability by utilizing cellular mobile network infrastructure. Additionally, this paper chronicles initial testbed development to meet this proposed architecture. Specific development of higher levels of autonomous swarms with UAV-to-UAV communication and coordination ability is central to advancing the utility of UAV swarms. The use of cellular mobile framework alleviates many limiting factors for UAVs including range of communication, networking challenges, size-weight-and-power (SWaP) considerations, while leveraging a robust and reliable infrastructure for machine to machine (M2M) communication proposed by 5G systems.

[1]  Robert W. Heath,et al.  Five disruptive technology directions for 5G , 2013, IEEE Communications Magazine.

[2]  Gary B. Lamont,et al.  UAV Swarm Mission Planning and Routing using Multi-Objective Evolutionary Algorithms , 2007, 2007 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making.

[3]  James S. Albus,et al.  Autonomy Levels For Unmanned Systems (ALFUS) framework, volume II :: framework models version 1.0 , 2007 .

[4]  Colin Keng-Yan Tan,et al.  UAV swarm coordination using cooperative control for establishing a wireless communications backbone , 2010, AAMAS.

[5]  James H. Oliver,et al.  UAV Swarm Control: Calculating Digital Pheromone Fields with the GPU , 2006 .

[6]  Emmanuel Lemoine,et al.  Amazon Prime Air , 2019 .

[7]  Prakash Ranganathan,et al.  Next generation distributed and networked autonomous vehicles: Review , 2018, 2018 10th International Conference on Communication Systems & Networks (COMSNETS).

[8]  Ilker Bekmezci,et al.  Flying Ad-Hoc Networks (FANETs): A survey , 2013, Ad Hoc Networks.

[9]  Cong Yan,et al.  A scalable architecture for ordered parallelism , 2015, 2015 48th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO).

[10]  Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles , 2022 .

[11]  Navrati Saxena,et al.  Next Generation 5G Wireless Networks: A Comprehensive Survey , 2016, IEEE Communications Surveys & Tutorials.

[12]  Florian Segor,et al.  Towards Autonomous Micro UAV Swarms , 2011, J. Intell. Robotic Syst..

[13]  Alessandro Matese,et al.  A flexible unmanned aerial vehicle for precision agriculture , 2012, Precision Agriculture.

[14]  Simon Bennertz,et al.  Combining UAV-based plant height from crop surface models, visible, and near infrared vegetation indices for biomass monitoring in barley , 2015, Int. J. Appl. Earth Obs. Geoinformation.

[15]  Erick Menezes Moreira,et al.  A surveillance task for a UAV in a natural disaster scenario , 2012, 2012 IEEE International Symposium on Industrial Electronics.

[16]  Eric W. Frew,et al.  Net-Centric Communication and Control for a Heterogeneous Unmanned Aircraft System , 2009, J. Intell. Robotic Syst..

[17]  Bill Canis Unmanned Aircraft Systems (UAS): Commercial Outlook for a New Industry , 2015 .

[18]  Luigi Barazzetti,et al.  Thermographic Analysis from UAV Platforms for Energy Efficiency Retrofit Applications , 2013, J. Mobile Multimedia.

[19]  Vera Stavroulaki,et al.  5G on the Horizon: Key Challenges for the Radio-Access Network , 2013, IEEE Vehicular Technology Magazine.

[20]  Robert H. Kewley,et al.  Swarming Unmanned Aircraft Systems , 2008 .

[21]  Marco Protti,et al.  UAV Autonomy - Which Level is Desirable? - Which Level is Acceptable? Alenia Aeronautica Viewpoint , 2007 .

[22]  Camille Alain Rabbath,et al.  Modeling of packet dropout for UAV wireless communications , 2012, 2012 International Conference on Computing, Networking and Communications (ICNC).

[23]  Tarik Taleb,et al.  Machine-type communications: current status and future perspectives toward 5G systems , 2015, IEEE Communications Magazine.

[24]  Jinqiang Cui,et al.  UAV LiDAR for below-canopy forest surveys , 2013 .

[25]  P. Rudol,et al.  Human Body Detection and Geolocalization for UAV Search and Rescue Missions Using Color and Thermal Imagery , 2008, 2008 IEEE Aerospace Conference.

[26]  D. Jones Power line inspection - a UAV concept , 2005 .

[27]  Ozgur Koray Sahingoz,et al.  Networking Models in Flying Ad-Hoc Networks (FANETs): Concepts and Challenges , 2013, Journal of Intelligent & Robotic Systems.

[28]  Nikolai Smolyanskiy,et al.  Toward low-flying autonomous MAV trail navigation using deep neural networks for environmental awareness , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[29]  Zhiqiang Wu,et al.  Performance evaluation of OFDM transmission in UAV wireless communication , 2005, Proceedings of the Thirty-Seventh Southeastern Symposium on System Theory, 2005. SSST '05..

[30]  C. Watson,et al.  Development of an Unmanned Aerial Vehicle (UAV) for hyper-resolution vineyard mapping based on visible, multispectral and thermal imagery , 2011 .

[31]  F. A. Vega,et al.  Multi-temporal imaging using an unmanned aerial vehicle for monitoring a sunflower crop , 2015 .

[32]  Guido Morgenthal,et al.  Quality Assessment of Unmanned Aerial Vehicle (UAV) Based Visual Inspection of Structures , 2014 .

[33]  James S. Albus,et al.  Toward a Generic Model for Autonomy Levels for Unmanned Systems (ALFUS) , 2003 .