Connectivity versus area coverage in unmanned aerial vehicle networks

We investigate the area coverage and connectivity of an autonomous, unmanned aerial vehicle (UAV) network, whose goal is to monitor and sense a given area of interest in an efficient manner. To this end, we propose a connectivity-based mobility model that aims to sustain connectivity between the UAVs and the ground station. We compare coverage and connectivity performance of the proposed scheme with a coverage-based mobility scheme in several scenarios. Results illustrate the trade-off between achieving good spatial coverage and staying connected.

[1]  Yasamin Mostofi,et al.  Communication-aware motion planning in fading environments , 2008, 2008 IEEE International Conference on Robotics and Automation.

[2]  Donald F. Towsley,et al.  Mobility improves coverage of sensor networks , 2005, MobiHoc '05.

[3]  J. Karl Hedrick,et al.  Autonomous UAV path planning and estimation , 2009, IEEE Robotics & Automation Magazine.

[4]  Paul Thompson,et al.  Mapping and Tracking , 2009, IEEE Robotics & Automation Magazine.

[5]  David W. Payton,et al.  Pheromone Robotics , 2001, Auton. Robots.

[6]  Howie Choset,et al.  Coverage for robotics – A survey of recent results , 2001, Annals of Mathematics and Artificial Intelligence.

[7]  Christian Bettstetter,et al.  Area Coverage with Unmanned Vehicles: A Belief-Based Approach , 2010, 2010 IEEE 71st Vehicular Technology Conference.

[8]  Guang Yang,et al.  Multi-agent control algorithms for chemical cloud detection and mapping using unmanned air vehicles , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[9]  Miodrag Potkonjak,et al.  Worst and best-case coverage in sensor networks , 2005, IEEE Transactions on Mobile Computing.

[10]  Christian Wietfeld,et al.  A communication aware steering strategy avoiding self-separation of flying robot swarms , 2010, 2010 5th IEEE International Conference Intelligent Systems.

[11]  Guoliang Xing,et al.  Integrated coverage and connectivity configuration in wireless sensor networks , 2003, SenSys '03.

[12]  Gaurav S. Sukhatme,et al.  Constrained coverage for mobile sensor networks , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[13]  William M. Spears,et al.  Distributed, Physics-Based Control of Swarms of Vehicles , 2004 .

[14]  Christian Bettstetter,et al.  Channel measurements over 802.11a-based UAV-to-ground links , 2011, 2011 IEEE GLOBECOM Workshops (GC Wkshps).

[15]  Dario Floreano,et al.  Communication-based Swarming for Flying Robots , 2010, ICRA 2010.

[16]  Alberto Elfes,et al.  Using occupancy grids for mobile robot perception and navigation , 1989, Computer.

[17]  Mario F. M. Campos,et al.  Decentralized motion planning for multiple robots subject to sensing and communication constraints , 2003 .

[18]  David Tse,et al.  Mobility increases the capacity of ad-hoc wireless networks , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[19]  Evsen Yanmaz,et al.  Stationary and Mobile Target Detection Using Mobile Wireless Sensor Networks , 2010, 2010 INFOCOM IEEE Conference on Computer Communications Workshops.