A Cooperative Network Framework for Multi-UAV Guided Ground Ad Hoc Networks
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  • 作者:Vishal Sharma (1)
    Rajesh Kumar (2)

    1. Department of Computer Science and Engineering
    ; Thapar University ; Patiala ; Punjab ; India
    2. School of Mathematics and Computer Applications
    ; Thapar University ; Patiala ; Punjab ; India
  • 关键词:Cooperative network ; Cognitive maps ; Ground Ad Hoc network ; Kalman Filter ; Topology organizing maps ; UAVs ad hoc network ; Neural network ; 11R52 ; 15A33 ; 62M45 ; 82C32
  • 刊名:Journal of Intelligent and Robotic Systems
  • 出版年:2015
  • 出版时间:March 2015
  • 年:2015
  • 卷:77
  • 期:3-4
  • 页码:629-652
  • 全文大小:4,992 KB
  • 参考文献:1. Zang, C., Zang, S.: Mobility prediction clustering algorithm for UAV networking. In: GLOBECOM Workshops. IEEE, pp. 1158鈥?161 (2011)
    2. Bekmezci, ., Sahingoz, O.K., Temel, .: Flying ad-hoc networks (FANETs): a survey. Ad Hoc Netw. 11(3), 1254鈥?270 (2013)
    3. Bellur, B., Lewis, M., Templin, F.: An ad-hoc network for teams of autonomous vehicles. In: Proceedings of the First Annual Symposium on Autonomous Intelligence Networks and Systems (2002)
    4. How, JP, Fraser, C, Kulling, KC, Bertuccelli, LF, Toupet, O, Brunet, L, Roy, N (2009) Increasing autonomy of UAVs, Robotics & Automation Magazine. IEEE 16: pp. 43-51
    5. Yang, Y., Minai, A., Polycarpou, M.M.: Evidential mapbuilding approaches for multi-UAV cooperative search. In: Proceedings of the American Control Conference, vol. 1, pp. 116 (2005)
    6. Hauert, S, Zufferey, JC, Floreano, D (2009) Evolved swarming without positioning information: an application in aerial communication relay. Auton. Robot. 26: pp. 21-32 CrossRef
    7. Lilien, L, Gupta, A, Kamal, ZE (2010) Opportunistic resource utilization networksA new paradigm for specialized ad hoc networks. Comput. Electr. Eng. 36: pp. 328-340 CrossRef
    8. Liu, M., Lin, J., Yuan, Y.: Research of UAV cooperative reconnaissance with self-organization path planning. In: International Conference on Computer, Networks and Communication Engineering, ICCNCE, Atlantis Press, pp. 207鈥?13 (2013)
    9. Lilien, LT, Ben Othmane, L, Angin, P, DeCarlo, A, Salih, RM, Bhargava, B (2013) A simulation study of ad hoc networking of UAVs with opportunistic resource utilization networks. J. Netw. Comput. Appl. 38: pp. 3-15 CrossRef
    10. Perez, D, Maza, I, Caballero, F, Scarlatti, D, Casado, E (2013) A ground control station for a multi-uav surveillance system. J. Intell. Robot. Syst. 69: pp. 119-130 CrossRef
    11. Cevik, P, Kocaman, I, Akgul, AS, Akca, B (2013) The small and silent force multiplier: a swarm UAVelectronic attack. J. Intell. & Robot. Syst. 70: pp. 595-608
    12. Gu, D.L., Pei, G., Ly, H., Gerla, M., Zhang, B., Hong, X.: UAV aided intelligent routing for ad-hoc wireless network in single-area theater, Wireless Communications and Networking Confernce, IEEE, vol. 3, pp. 1220鈥?225 (2000)
    13. Capitn, J, Merino, L, Caballero, F, Ollero, A (2011) Decentralized delayed-state information filter (DDSIF): A new approach for cooperative decentralized tracking. Robot. Auton. Syst. 59: pp. 376-388 CrossRef
    14. Dressler, F, Akan, OB (2010) A survey on bio-inspired networking. Comput. Netw. 54: pp. 881-900 CrossRef
    15. Muller, M.: Flying Ad-Hoc Networks, Institute of Media Informatics Ulm University, pp. 53鈥?9 (2012)
    16. Li, J., Zhou, Y., Lamont, L., Toulgoat, M., Rabbath, C.A.: Packet Delay in UAV Wireless Networks Under Nonsaturated Traffic and Channel Fading Conditions, Wireless Personal Communications, pp. 1鈥?9 (2013)
    17. Yang, Y, Polycarpou, MM, Minai, AA (2007) Multi-UAV cooperative search using an opportunistic learning method. Trans. ASME 129: pp. 716 CrossRef
    18. Polycarpou, M.M., Yang, Y., Passino, K.M.: A cooperative search framework for distributed agents, Intelligent Control, (ISIC鈥?1). In: Proceedings of the IEEE International Symposium, pp. 1鈥? (2001)
    19. Trawny, N., Roumeliotis, S.I.: Indirect Kalman filter for 3D attitude estimation, University of Minnesota, Department Computer Science & Engineering Technical Report, pp. 2 (2005)
    20. Meinhold, RJ, Singpurwalla, ND (1983) Understanding the Kalman filter. Am. Stat. 37: pp. 123-127
    21. Benini, A, Mancini, A, Longhi, S (2013) An IMU/UWB/Vision-based Extended Kalman Filter for Mini-UAV Localization in Indoor Environment using 802.15. 4a Wireless Sensor Network. J. Intell. Robot. Syst. 70: pp. 461-476 CrossRef
    22. Sakhaee, E., Jamalipour, A., Kato, N.: Aeronautical ad hoc networks. Wireless Communications and Networking Conferece, IEEE, pp. 246鈥?51 (2006)
    23. Iordanakis, M., Yannis, D., Karras, K., Bogdos, G., Dilintas, G., Amirfeiz, M., Baiotti, S.: Ad-hoc routing protocol for aeronautical mobile ad-hoc networks. Fifth International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP) (2006)
    24. Paunicka, J.L., Corman, D.E., Mendel, B.R.: A CORBA based middleware solution for UAVs. In: Object-Oriented Real-Time Distributed Computing, ISORC- Proceedings. Fourth IEEE International Symposium, pp. 261鈥?67 (2001)
    25. Palazzi, CE, Roseti, C, Luglio, M, Gerla, M, Sanadidi, MY, Stepanek, J (2005) Enhancing transport layer capability in HAPSSatellite integrated architecture. Wirel. Pers. Commun. 32: pp. 339-356 CrossRef
    26. Palazzi, C.E., Roseti, C., Luglio, M., Gerla, M., Sanadidi, M.Y., Stepanek, J.: Satellite coverage in urban areas using Unmanned Airborne Vehicles (UAVs). In: Vehicular Technology Conference, IEEE 59th, Vol. 5, pp. 2886鈥?890 (2004)
    27. Allred, J., Hasan, A.B., Panichsakul, S., Pisano, W., Gray, P., Huang, J., Mohseni, K.: Sensorflock: an airborne wireless sensor network of micro-air vehicles. In: Proceedings of the 5th International Conference on Embedded Networked Sensor Systems (2007)
    28. Ajami, A., Balmat, J.F., Gauthier, J.P., Maillot, T.: Path planning and Ground Control Station simulator for UAV. Aerospace Conference, IEEE, pp. 1鈥?3 (2013)
    29. Craighead, J., Murphy, R., Burke, J., Goldiez, B.: A survey of commercial & open source unmanned vehicle simulators. Robotics and Automation, IEEE International Conference, pp. 852鈥?57 (2007)
    30. Lin, L, Sun, Q, Li, J, Yang, F (2012) A novel geographic position mobility oriented routing strategy for UAVs. J. Comput. Inf. Syst. 8: pp. 709-716
    31. Bellur, B., Ogier, R.G.: A reliable, efficient topology broadcast protocol for dynamic networks. In: INFOCOM鈥?9. Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies, vol. 1, pp. 178鈥?86 (1999)
    32. Rysdyk, R.: UAV path following for constant line-of-sight. In: 2nd AIAA Unmanned Unlimited. Conference and Work shop and Exhibit, San Diego, CA (2003)
    33. Akbas, M.I., Turgut, D.: APAWSAN: Actor positioning for aerial wireless sensor and actor networks. In: Local Computer Networks (LCN), IEEE 36th Conference. pp. 563鈥?70 (2011)
    34. Aggarwal, P., Syed, Z., Niu, X., El-Sheimy, N.: Cost effective testing and calibration of low cost MEMS sensors for integrated positioning, navigation and mapping systems. In: Proceedings of XIII FIG Conference, pp. 8鈥?3 (2006)
    35. Jung, D., Tsiotras, P.: Inertial attitude and position reference system development for a small UAV, AIAA Infotech at aerospace. pp. 7鈥?0 (2007)
    36. Durham, C.M., Andel, T.R., Hopkinson, K.M., Kurkowski, S.H.: Evaluation of an OPNET model for unmanned aerial vehicle (UAV) networks. In: Proceedings of the Spring Simulation Multiconference, pp. 66 (2009)
    37. Morse, B.S., Engh, C.H., Goodrich, M.A.: UAV video coverage quality maps and prioritized indexing for wilderness search and rescue. In: Proceedings of the 5th ACM/IEEE International Conference on Human-robot Interaction, pp. 227鈥?34 (2010)
    38. Lpez, J., Royo, P., Pastor, E., Barrado, C., Santamaria, E.: A middleware architecture for unmanned aircraft avionics. In: Proceedings of the 2007 ACM/IFIP/USENIX International Conference on Middleware Companion. pp. 24 (2007)
    39. Perkins, C.E., Royer, E.M.: Ad-hoc on-demand distance vector routing. In: Mobile Computing Systems and Applications, Proceedings, WMCSA鈥?9, Second IEEE Workshop, pp. 90鈥?00 (1990)
    40. Konishi, K., Maeda, K., Sato, K., Yamasaki, A., Yamaguchi, H., Yasumoto, K., Higashino, T.: Mobireal simulator-evaluating manet applications in real environments. In: 13th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, pp. 499鈥?02 (2005)
    41. Abdessameud, A, Tayebi, A (2010) Global trajectory tracking control of VTOL-UAVs without linear velocity measurements. Automatica 46: pp. 1053-1059 CrossRef
    42. Yamasaki, T., Sakaida, H., Enomoto, K., Takano, H., Baba, Y.: Robust trajectory-tracking method for UAV guidance using proportional navigation. In: International Conference on Control, Automation and Systems, ICCAS鈥?7, pp. 1404鈥?409 (2007)
    43. Zhan, P., Casbeer, D., Swindlehurst, A.L.: A centralized control algorithm for target tracking with UAVs. Conference Record of the 39th Asilomar Conference on Signals, Systems and Computers, pp. 1148鈥?152 (2005)
    44. Karras, K., Kyritsis, T., Amirfeiz, M., Baiotti, S.: Aeronautical mobile Ad hoc networks, Wireless Conference, EW, 14th European, IEEE, pp. 1鈥? (2008)
    45. Miles, J, Kamath, G, Muknahallipatna, S, Stefanovic, M, Kubichek, RF (2013) Optimal trajectory determination of a single moving beacon for efficient localization in a mobile ad-hoc network. Ad Hoc Netw. 11: pp. 238-256 CrossRef
    46. Niculescu, D, Nath, B (2003) DV based positioning in ad hoc networks. Telecommun. Syst. 22: pp. 267-280 CrossRef
    47. Cetin, O, Zagli, I, Yilmaz, G (2013) Establishing Obstacle and Collision Free Communication Relay for UAVs with Artificial Potential Fields. J. Intell. Robot. Syst. 69: pp. 361-372 CrossRef
    48. Jensen, A., Chen, Y.: Tracking tagged fish with swarming Unmanned Aerial Vehicles using fractional order potential fields and Kalman filtering. Unmanned Aircraft Systems (ICUAS), International Conference, pp. 1144鈥?149 (2013)
    49. Valavanis, K.P.: Advances in unmanned aerial vehicles: state of the art and the road to autonomy, vol. 33. Springer (2007)
    50. Rubin, I., Behzad, A., Ju, H.J., Zhang, R., Huang, X., Liu, Y., Khalaf, R.: Ad hoc wireless networks with mobile backbones. In: 15th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC, vol. 1, pp. 566鈥?73 (2004)
    51. Jara, CA, Candelas, FA, Gil, P, Torres, F, Esquembre, F, Dormido, S (2011) Ejs+ EjsRL: An interactive tool for industrial robots simulation, Computer Vision and remote operation. Robot. Auton. Syst. 59: pp. 389-401 CrossRef
    52. Zhang, G., Yang, K., Liu, P., Feng, X.: Incentive Mechanism for Multiuser Cooperative Relaying in Wireless Ad Hoc Networks: A Resource-Exchange Based Approach, Wireless Personal Communications, pp. 1鈥?9 (2013)
    53. Levin, L, Segal, M, Shpungin, H (2013) Cooperative data collection in ad hoc networks. Wirel. Netw. 19: pp. 145-159 CrossRef
    54. Carpenter, G.A., Grossberg, S.: ART 2: Self-organization of stable category recognition codes for analog input patterns. In: Robotics and IECON Conferences, International Society for Optics and Photonics, pp. 272鈥?80 (1988)
    55. Acharya, T, Paul, G (2013) Maximum Lifetime Broadcast Communications in Cooperative Multihop Wireless Ad Hoc Networks: Centralized and Distributed Approaches. Ad Hoc Netw. 11: pp. 1667-1682 CrossRef
  • 刊物类别:Engineering
  • 刊物主题:Automation and Robotics
    Electronic and Computer Engineering
    Artificial Intelligence and Robotics
    Mechanical Engineering
  • 出版者:Springer Netherlands
  • ISSN:1573-0409
文摘
Cooperative ad hoc networks are becoming very important in various military and civilian applications. The interfacing between different ad hoc networks provides large applications in field of surveillance, navigation, disaster monitoring and homeland security. This paper focuses on implementation of UAV (unmanned aerial vehicles) ad hoc network that forms a guidance system for ground ad hoc network. The network framework proposed in the paper uses neural network to form cognitive and topology maps. Indirect and Bayesian Kalman Filter are used for estimations. These estimations allows updating of pre-constructed cognitive map to form ideal final search map that is shared among all nodes to perform search and track operations. The analysis showed that the proposed framework is capable of forming a search maps that is able to define multiple way points for each UAV in the network to follow a non-redundant path for searching and identifying various user nodes and geographical territories. The effectiveness of the model is demonstrated using simulations.

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