Heuristic optimization technique to locate and avoid buried landmines: drone-based approach
Автор: Abdel Ilah N. Alshbatat
Журнал: International Journal of Information Technology and Computer Science @ijitcs
Статья в выпуске: 11 Vol. 10, 2018 года.
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Landmines detection and removal are one of the biggest problems that faced many countries throughout the world. The procedures of landmines detection and removal are slow, dangerous and labor intensive. Some countries are currently involved in peacekeeping forces, where troops are in constant danger from landmines placed along roads and tracks. Accordingly, such traps are considered as an effective weapon in threatening troop’s lives, and preventing their movements. From this perspective, to meet the need for a fast way to locate landmines, and to offer the highest level of safety for military forces without the risk of triggering them during any mission; a lightweight aerial system that implements a heuristic optimization technique is proposed in this paper. The system is structured with five units: Hexacopter unmanned aerial vehicle (UAV), landmine detector, hands free flight controller, emergency flight controller, and the main on-board flight controller. Drone is equipped with a landmine detector, emergency flight controller, and the main on-board flight controller. Based on the feedback from the landmine detector, Drone will guide the leader of the troop through the communication channel established between the hands free flight controller and the emergency flight controller. The system has been simulated using the MATLAB and the overall concept shows promise. Additionally, experiments are carried out successfully on the real hardware.
Drone, Hexacopter Unmanned Aerial Vehicle, Landmines, Landmine Detector, Flight Controller
Короткий адрес: https://sciup.org/15016314
IDR: 15016314 | DOI: 10.5815/ijitcs.2018.11.05
Список литературы Heuristic optimization technique to locate and avoid buried landmines: drone-based approach
- H. Frigui, and P. Gader, “Detection and Discrimination of Land Mines in Ground-Penetrating Radar Based on Edge Histogram Descriptors and a Possibilistic K-Nearest Neighbor Classifier,” IEEE Transactions on Fuzzy Systems, Volume: 17, Issue: 1, PP. 185-199, 2009.
- A. vishnoi, D. shinghal, A. kumar, A. pal, and D. sisonia, “A Critique Study on Autonomous Wireless Warfield Explosives Detection System,” International Journal of Advanced Computational Engineering and Networking, ISSN: 2320-2106, Volume-4, Issue-11, Nov.-2016.
- S. Kaya, U. M. Leloglu, “Buried and Surface Mine Detection from Thermal Image Time Series,” IEEE J. Sel. Topics Appl. Earth Observations Remote Sens., vol. 10, no. 10, pp. 4544-4552, Oct. 2017.
- I. Giannakis, A. Giannopoulos and C. Warren, “A Realistic FDTD Numerical Modeling Framework of Ground Penetrating Radar for Landmine Detection,” IEEE J. Sel. Topics Appl. Earth Observations in Remote Sens., vol. PP, no. 99, pp. 1-15, 2015.
- E. Rosen and K. Sherbondy, “Performance Assessment of Mine Detection Systems,” Proc. SPIE 4038, Detection and Remediation Technologies for Mines and Mine like Targets, 22 August 2000.
- H. Bass, L. Bolen, D. Cress, J. Lundien, and M. Flohr, “Coupling of Airborne Sound into the Earth: Frequency Dependence,” Journal of the Acoustical Society of America 67, pp. 1502-1506, 1980.
- J. Sabatier, H. Bass, L. Bolen, and K. Attenborough, “Acoustically Divided Seismic Waves,” Journal of the Acoustical Society of America 80, pp. 646-649, 1986.
- J. Sabatier, H. Bass, L. Bolen, K. Attenborough, and V. Sastry, “The Interaction of Airborne Sound with the Porous Ground. The Theoretical Formulation,” Journal of the Acoustical Society of America 79, pp. 1345-1352, 1986.
- J. Sabatier, H. Hess, W. Arnott, K. Attenborough, M. Roemkens and E. Grissinger, “In-Situ Measurements of Soil Physical Properties by Acoustical Techniques,” Soil Science Society of America Journal, Vol. 54 No. 3, p. 658-672, 1990.
- C. Hickey, and J. Sabatier, “Measurements of Two Types of Dilatational Waves in an Air-filled Unconsolidated Sand,” Journal of the Acoustical Society of America 102, pp. 128-136, 1997.
- H. Bass, and J. M. Sabatier, “Acoustic to Seismic Coupling and Physical Measurements,” Proc. SPIE Conference on Detection and Remediation Technologies for Mines and Mine like Targets, pp. 4038-69, 2000.
- J. Sabatier and K. Gilbert, “Method for Detecting Buried Object by Measuring Seismic Vibrations Induced by Acoustical Coupling with a Remote Source of Sound,” U.S. Patent 6 081 481, 2000.
- D. Sipos, P. Planinsic, D. Gleich, “On Drone Ground Penetrating Radar for Landmine Detection,” Proc. 1st Int. Conf. Landmine: Detection Clearance Legislations (LDCL), pp. 1-4, Apr. 2017.
- J. Colorado et al., “An Integrated Aerial System for Landmine Detection: SDR-based Ground Penetrating Radar Onboard an Autonomous Drone,” Adv. Robot., vol. 31, no. 15, pp. 791-808, 2017.
- J. Colorado, C. Devia, M. Perez, I. Mondragon, D. Mendez, and C. Parra, “Low-altitude Autonomous Drone Navigation for Landmine Detection Purposes,” International Conference on Unmanned Aircraft Systems (ICUAS) June 13-16, 2017, Miami, FL, USA.
- J. Rodriguez, C. Castiblanco, I. Mondragon, and J. Colorado, “Low-cost Quadrotor Applied for Visual Detection of Landmine-like Objects,” In International Conference on Unmanned Aircraft Systems -ICUAS, pp. 83–88, 2014.
- M. McCartney, S. Zein-Sabatto, and M. Malkani, “Image Registration for Sequence of Visual Images Captured by UAV,” In IEEE Symposium on Computational Intelligence for Multimedia Signal and Vision Processing, 2009.
- A. Amiri, K. Tong, and K. Chetty, “Feasibility Study of Multi-frequency Ground Penetrating Radar for Rotary UAV Platforms,” IET International Conference on Radar Systems, pp.1284–1290, 2012.
- C. Goerzen, Z. Kong, and B. Mettler, “A survey of Motion Planning Algorithms from the Perspective of Autonomous UAV Guidance,” Journal of Intelligent and Robotic Systems, 57(1-4), pp. 65–100, 2010.
- F. Bourgault, T. Furukawa, and H. Durrant-Whyte, “Optimal Search for a Lost Target in a Bayesian World,” Springer Tracts in Advanced Robotics, vol. 24. New York, NY, USA: Springer-Verlag, 2006, ch. 21, pp. 209–222.
- L. Lin and M. Goodrich, “UAV Intelligent Path Planning for Wilderness Search and Rescue,” in Proc. IROS, Oct. 2009, pp. 709–714.
- E. Dijkstra, “A note on Two Problems in Connection with Graphs,” Numerische Mathematik, Vol. 1, PP. 269-271, 1959.
- L. Byunghee, K. Kabil, “Path Planning Algorithm Using the Particle Swarm Optimization and the Improved Dijkstra Algorithm,” In Proceedings of IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application, Wuhan, China, 19–20 December 2008; Volume 2, pp. 1002–1004.
- P. Hart, N. Nilsson, B. Raphael, “A formal Basis for the Heuristic Determination of Minimum Cost Paths,” IEEE Trans. Syst. Sci. Cybern. SCC-4(2), 100–107 (1968).
- D. Ferguson, A. Stentz, “Using Interpolation to Improve Path Planning: the Field D* Algorithm,” J. Field Robot. 23(2), 79–101 (2006).
- A. Nash, K. Daniel, S. Koenig, A. Felner, “Theta*: Any-Angle Path Planning on Grids,” In Proceedings of the AAAI Conference on Artificial Intelligence, pp. 1177–1183 (2007).
- G. Timothy, McGee, and J. Karl Hedrick, “Optimal Path Planning with a Kinematic Airplane Model,” Journal of Guidance, Control, and Dynamics, Vol. 30, No. 2 (2007), pp. 629-633.
- Gu. DW, I. Postlethwaite, Y. Kim, “A Comprehensive Study on Flight Path Selection Algorithms,” In the IEE seminar on target tracking: algorithms and applications, Birmingham, UK. Piscataway: Institution of Electrical Engineers; 2006. p. 77–90.
- O. Meister, N. Frietsch, C. Ascher, G. Trommer, “Adaptive Path Planning for VTOL-UAVs,” IEEE Aerospace Electron System Mag, 24 (7) (2009), pp. 36-41.
- V. Artale, C. Milazzo, A. Ricciardello, “Mathematical Modeling and Control of a Hexacopter,” Applied Mathematical Sciences, Vol. 7, 2013, no. 97, pp.4805 – 4811.