**Page description appears here**

“Autonomous Aerial Ice Observation for Ice Defense”

Authors: Joakim Haugen and Lars Imsland,
Affiliation: NTNU, Department of Engineering Cybernetics
Reference: 2014, Vol 35, No 4, pp. 279-291.

     Valid XHTML 1.0 Strict


Keywords: Automated guided vehicles; dynamic coverage control, ice observation; multitarget tracking

Abstract: One of the tasks in ice defense is to gather information about the surrounding ice environment using various sensor platforms. In this manuscript we identify two monitoring tasks known in literature, namely dynamic coverage and target tracking, and motivate how these tasks are relevant in ice defense using RPAS. An optimization-based path planning concept is outlined for solving these tasks. A path planner for the target tracking problem is elaborated in more detail and a hybrid experiment, which consists of both a real fixed-wing aircraft and simulated objects, is included to show the applicability of the proposed framework.

PDF PDF (2916 Kb)        DOI: 10.4173/mic.2014.4.5



DOI forward links to this article:
  [1] Roger Skjetne, Lars Imsland and Sveinung LÝset (2014), doi:10.4173/mic.2014.4.1


References:
[1] AMOS. (2014). Center for Autonomous Marine Operations and Systems, 2014. http://www.ntnu.edu/amos/centre-for-autonomous-marine-operations-and-systems.
[2] Andersson, J., Aakesson, J., and Diehl, M. (2012). CasADi: A symbolic package for automatic differentiation and optimal control, In S.Forth, P.Hovland, E.Phipps, J.Utke, and A.Walther, editors, Recent Advances in Algorithmic Differentiation, volume87 of Lecture Notes in Computational Sci. and Eng., pages 297--307. Springer-Verlag, Berlin Heidelberg, Germany. doi:10.1007/978-3-642-30023-3_27
[3] Arctic Marine Solutions. (2014). 2014, www.arcticmarinesolutions.se.
[4] Biegler, L.T. (2010). Nonlinear Programming: Concepts, Algorithms & Applications to Chemical Processes, SIAM, Philadelphia, PA. doi:10.1137/1.9780898719383
[5] Burns, J.A., Cliff, E.M., and Rautenberg, C. (2009). A distributed parameter control approach to optimal filtering and smoothing with mobile sensor networks, In Proc. 17th Mediterranean Conf. Control & Automation, MED '09. Thessaloniki, Greece, pages 181--186. doi:10.1109/MED.2009.5164536
[6] CAA--Norway. (2014). Civil Aviation Authority -- Norway, RPAS-FAQ, 2014. www.luftfartstilsynet.no/selvbetjening/allmennfly/RPAS-FAQ/.
[7] Choi, H. and How, J.P. (2010). Continuous trajectory planning of mobile sensors for informative forecasting, Automatica. 46(8):1266--1275. doi:10.1016/j.automatica.2010.05.004
[8] Cloud Cap Technology. (2013). 2013, http://www.cloudcaptech.com.
[9] Crowe, W., Davis, K.D., la Cour-Harbo, A., Vihma, T., Lesenkov, S., Eppi, R., Weatherhead, E.C., Liu, P., Raustein, M., Abrahamsson, M., Johansen, K.-S., and Marshall, D. (2012). Enabling science use of unmanned aircraft systems for arctic environmental monitoring, Technical Report6, Arctic Monitoring and Assessment Programme (AMAP), Oslo, Norway. http://amap.no/documents/download/938.
[10] Demetriou, M.A. (2010). Guidance of mobile actuator-plus-sensor networks for improved control and estimation of distributed parameter systems, IEEE Trans. Autom. Control. 55(7):1570--1584. doi:10.1109/TAC.2010.2042229
[11] Demetriou, M.A. and Hussein, I.I. (2009). Estimation of spatially distributed processes using mobile spatially distributed sensor network, SIAM J. Control Optim.. 48(1):266--291. doi:10.1137/060677884
[12] Edmond, C., Liferov, P., and Metge, M. (2011). Ice and iceberg management plans for shtokman field, In Proc. OTC Arctic Technol. Conf. 2011. Houston, TX, pages 1--9. doi:10.4043/22103-MS
[13] Eik, K. (2008). Review of experiences within ice and iceberg management, J. Navig.. 61(4):557--572. doi:10.1017/S0373463308004839
[14] Eik, K. and Loset, S. (2009). Specification for a subsurface ice intelligence system, In Proc. ASME 28th Int. Conf. Ocean, Offshore and Arctic Eng., OMAE2009. Honolulu, HI, pages 103--109. doi:10.1115/OMAE2009-79606
[15] Fossen, T.I. (2011). Handbook of Marine Craft Hydrodynamics and Motion Control, John Wiley & Sons Inc., Hoboken, NJ. doi:10.1002/9781119994138
[16] Frew, E.W. and Brown, T.X. (2009). Networking issues for small unmanned aircraft systems, J. Intell. Robot. Syst.. 54(1--3):21--37. doi:10.1007/s10846-008-9253-2
[17] Gurtner, A., Baardson, B. H.H., Kaasa, G.-O., and Lundin, E. (2012). Aspects of importance related to arctic dp operations, In Proc. ASME 31th Int. Conf. Ocean, Offshore and Arctic Eng., OMAE2012. Rio de Janeiro, Brazil, pages 617--623. doi:10.1115/OMAE2012-84226
[18] Hamilton, J., Holub, C., Blunt, J., Mitchell, D., and Kokkinis, T. (2011). Ice management for support of arctic floating operations, In Proc. OTC Arctic Technol. Conf. 2011. Houston, TX, pages 1--12. doi:10.4043/22105-MS
[19] Haugen, J., Grotli, E.I., and Imsland, L. (2012). State estimation of ice thickness distribution using mobile sensors, In Proc. IEEE Multi-Conf. Syst. Control. Dubrovnik, Croatia, pages 336--343. doi:10.1109/CCA.2012.6402649
[20] Haugen, J. and Imsland, L. (2013). Optimization-based autonomous remote sensing of surface objects using an unmanned aerial vehicle, In Proc. European Control Conf. (ECC). Zurich, Switzerland, pages 1242--1249, 2013. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6669610.
[21] Haugen, J. and Imsland, L. (2013). UAV Path Planning for Multitarget Tracking with Experiments, In Proc. 2nd IFAC Workshop Res., Develop. and Educ. Unmanned Aerial Syst. Compi`egne, France, pages 316--323, 2013. doi:10.3182/20131120-3-FR-4045.00061
[22] Haugen, J. and Imsland, L. (2014). Monitoring an advection-diffusion process using aerial mobile sensors, Unmanned Systems, 2014. Submitted.
[23] Haugen, J. and Imsland, L. (2014). Monitoring moving objects using aerial mobile sensors, IEEE Trans. Control Syst. Technol., 2014. Accepted.
[24] Haugen, J., Imsland, L., Loset, S., and Skjetne, R. (2011). Ice observer system for ice management operations, In Proc. 21st Int. Offshore and Polar Eng. Conf. Maui, HI, pages 1120--1127.
[25] Hindmarsh, A.C., Brown, P.N., Grant, K.E., Lee, S.L., Serban, R., Shumaker, D.E., and Woodward, C.S. (2005). SUNDIALS : Suite of nonlinear and differential / algebraic equation solvers, ACM T. Math. Software. 31(3):363--396. doi:10.1145/1089014.1089020
[26] HSL. (2011). A collection of Fortran codes for large scale scientific computation, 2011. http://www.hsl.rl.ac.uk.
[27] Keinonen, A.J. (2008). Ice management for ice offshore operations, In Proc. OTC Arctic Technol. Conf. 2008. Houston, TX, pages 1--15. doi:10.4043/19275-MS
[28] Looker, J.R. (2008). Minimum paths to interception of a moving target when constrained by turning radius, Technical Report DSTO-TR-2227, Defence Sci. & Technol. Organisation, Canberra, Australia. http://dspace.dsto.defence.gov.au/dspace/bitstream/1947/9741/1/DSTO-TR-222, PR.pdf.
[29] Maritime Robotics. (2013). 2013, http://www.maritimerobotics.com.
[30] Metrikin, I., Loset, S., Jenssen, N.A., and Kerkeni, S. (2013). Numerical simulation of dynamic positioning in ice, Marine Technol. Soc. J.. 47(2):14--30. doi:10.4031/MTSJ.47.2.2
[31] Moran, K., Backman, J., and Farrell, J.W. (2006). Deepwater drilling in the arctic ocean's permanent sea ice, In J.Backman, K.Moran, D.B. McInroy, L.A. Mayer, and the Expedition 302 Scientists, editors, Proc. IODP, 302. Integraded Ocean Drilling Program Management Int., Inc., Edinburgh, UK, pages 1--13. doi:10.2204/iodp.proc.302.106.2006
[32] Morbidi, F. and Mariottini, G.L. (2013). Active target tracking and cooperative localization for teams of aerial vehicles, IEEE Trans. Control Syst. Technol.. 21(5):1694--1707. doi:10.1109/TCST.2012.2221092
[33] Norut. (2014). Norut UAV remote sensing, 2014. http://norut.no/en/satelitter-fjernmaling-og-ubemannede-fly.
[34] Parker, L.E. (1999). Cooperative robotics for multi-target observation, Intell. Autom. Soft Comput.. 5(1):5--19. doi:10.1080/10798587.1999.10750747
[35] Rathinam, S., Sengupta, R., and Darbha, S. (2007). A resource allocation algorithm for multivehicle systems with nonholonomic constraints, IEEE Trans. Autom. Sci. Eng.. 4(1):98--104. doi:10.1109/TASE.2006.872110
[36] Savla, K., Frazzoli, E., and Bullo, F. (2008). Traveling salesperson problems for the Dubins vehicle, IEEE Trans. Autom. Control. 53(6):1378--1391. doi:10.1109/TAC.2008.925814
[37] Sheykin, I.B. (2010). Icebreaker reconnaissance for ice mangement: offshore experience, In Proc. 20th IAHR Int. Symp. Ice. Lahti, Finland, pages 525--536.
[38] Simicon. (2011). Simicon Arctic UAS, 2011. http://simicon.no/.
[39] Simon, D. (2006). Optimal State Estimation, John Wiley & Sons Inc., Hoboken, NJ.
[40] Tang, Z. and Ozguner, U. (2005). Motion planning for multitarget surveillance with mobile sensor agents, IEEE Trans. Robot.. 21(5):898--908. doi:10.1109/TRO.2005.847567
[41] Tricaud, C. and Chen, Y. (2012). Optimal Mobile Sensing and Actuation Policies in Cyber-physical Systems, Springer-Verlag, London, UK. doi:10.1007/978-1-4471-2262-3_1
[42] UAV Factory. (2013). 2013, http://www.uavfactory.com.
[43] Waechter, A. and Biegler, L.T. (2006). On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming, Math. Programming. 106:25--57. doi:10.1007/s10107-004-0559-y
[44] Wang, Y. and Hussein, I.I. (2012). Search and Classification Using Multiple Autonomous Vehicles, Springer-Verlag, London, UK. doi:10.1007/978-1-4471-2957-8_1
[45] Xianyi, Z., Qian, W., and Yunquan, Z. (2012). Model-driven level 3 BLAS performance optimization on Loongson 3A processor, In Proc. IEEE 18th Int. Conf. Parallel and Distributed Syst. (ICPADS). Singapore, pages 684--691. doi:10.1109/ICPADS.2012.97


BibTeX:
@article{MIC-2014-4-5,
  title={{Autonomous Aerial Ice Observation for Ice Defense}},
  author={Haugen, Joakim and Imsland, Lars},
  journal={Modeling, Identification and Control},
  volume={35},
  number={4},
  pages={279--291},
  year={2014},
  doi={10.4173/mic.2014.4.5},
  publisher={Norwegian Society of Automatic Control}
};

News

May 2016: MIC reaches 2000 DOI Forward Links. The first 1000 took 34 years, the next 1000 took 2.5 years.


July 2015: MIC's new impact factor is now 0.778. The number of papers published in 2014 was 21 compared to 15 in 2013, which partially explains the small decrease in impact factor.


Aug 2014: For the 3rd year in a row MIC's impact factor increases. It is now 0.826.


Dec 2013: New database-driven web-design enabling extended statistics. Article number 500 is published and MIC reaches 1000 DOI Forward Links.


Jan 2012: Follow MIC on your smartphone by using the RSS feed.

Smartphone


July 2011: MIC passes 1000 ISI Web of Science citations.


Mar 2010: MIC is now indexed by DOAJ and has received the Sparc Seal seal for open access journals.


Dec 2009: A MIC group is created at LinkedIn and Twitter.


Oct 2009: MIC is now fully updated in ISI Web of Knowledge.