[Studies in Computational Intelligence 481] Artur Babiarz, Robert Bieda, Karol Jędrasiak, Aleksander Nawrat (auth.), Aleksander Nawrat, Zygmunt Kuś (eds.) - Vision Based Systemsfor UAV Applications (2013, Sprin

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200 D. Cedrych et al. Table 1. Indices values of UAV path for Simulation number 1 2722 3602 800 2 3900 4983 1500 3 3293 4241 1150 4 3530 4616 1300 5 3140 3761 800 Average value 3317 4240 1100 Table 2. Indices values of UAV path for Simulation number 1 2791 3187 750 2 3743 4170 850 3 2574 3021 750 4 3131 3921 950 5 2991 3381 750 Average value 3046 3536 810 Table 3. Indices values of UAV path for Simulation number 1 3219 3500 750 2 2700 3057 750 3 2661 2837 550 4 3055 3491 650 5 3054 2520 950 Average value 2937.8 3281 730 4 Conclusions In this chapter set of simulations that generates solution of the problem of collision free path planning in 3D space was presented. The target application of the discussed method is determination of the way points of the flight of the UAV. Presented approach allows to find feasible path in 3D space simultaneously reducing the computations. Thanks to the simplification that consists in splitting the process on two stages the method is both effective and simple (in terms of computation costs). The simplicity was the one of the most important assumptions taken for the design of the UAV control system. Since the method is not deterministic it generates different solutions. After a number of simulations it was checked that all the generated solutions are also feasible ones and they are satisfactory for the overall UAV control system.
Probabilistic Approach to Planning Collision Free Path of UAV 201 Acknowledgment. This work has been supported in part by Ministry of Science and Higher Education funds in the year 2013 as development project OR00013212. References [1] Adolf, F.M., Hirschmuller, H.: Meshing and Simplification of High Resolution Urban Surface Data for UAV Path Planning. Journal of Intelligent and Robotic Systems 61, 169–180 (2011) [2] Barraquand, J., Kavraki, L., Latombe, J.C., Motwani, R., Li, T.Y., Raghavan, P.: A random sampling scheme for path planning. International Journal of Robotics Research 16, 759–774 (1997) [3] Barraquand, J., Langlois, B., Latombe, J.C.: Numerical Potential-Field Techniques for Robot Path Planning. IEEE Transactions on Systems Man and Cybernetics 22, 224–241 (1992) [4] Cedrych, D.: Poszukiwanie trajektorii bezzaogowego obiektu latającego w przestrzeni 3D z wykorzystaniem elementów teorii grafów. Unpublished engineer project, Silesian University of Technology (2011) (in polish) [5] Deo, N.: Graph Theory with Applications to Engineering and Computer Science. Prentice Hall Series in Automatic Computation (1974) [6] Fujimura, K., Samet, H.: A Hierarchical Strategy for Path Planning Among Moving Obstacles. IEEE Transactions on Robotics and Automation 5, 61–69 (1989) [7] Ge, S.S., Cui, Y.J.: New Potential Functions for Mobile Robot Path Planning. IEEE Transactions on Robotics and Automation 16, 615–620 (2000) [8] Hsu, D., Latombe, J.C., Motwani, R.: Path Planning in Expansive configuration spaces. International Journal of Computational Geometry and Applications 9, 495– 512 (1999) [9] Hwang, Y.K., Ahuja, N.: A Potential-Field Approach to Path Planning. IEEE Transactions on Robotics and Automation 8, 23–32 (1992) [10] Kambhampati, S., Davis, L.S.: Multiresolution Path Planning for Mobile Robots. IEEE Journal of Robotics and Automation 2, 135–145 (1986) [11] Kant, K., Zucker, S.W.: Toward Efficient Trajectory Planning - the Path-Velocity Decomposition. International Journal of Robotics Research 5, 72–89 (1986) [12] Kavraki, L.E., Kolountzakis, M.N., Latombe, J.C.: Analysis of Probabilistic Roadmaps for Path Planning. IEEE Transactions on Robotics and Automation 14, 166– 171 (1998) [13] Kavraki, L.E., Svestka, P., Latombe, J.C., Overmars, M.H.: Probabilistic Roadmaps for Path Planning in High-Dimensional Configuration spaces. IEEE Transactions on Robotics and Automation 12, 566–580 (1996) [14] LaValle, S.M.: Planning Algorithms. Cambridge University Press (2006) [15] Lumelsky, V.J., Mukhopadhyay, S., Sun, K.: Dynamic Path Planning in Sensor- Based Terrain Acquisition. IEEE Transactions on Robotics and Automation 6, 462– 472 (1990)
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Studies in Computational Intelligen
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Aleksander Nawrat · Zygmunt Kuś E
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“In God We Trust, All others we o
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VIII Preface valuable information i
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Contents Part I: Design of Object D
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Contents XIII Technology Developmen
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XVI List of Contributors Adam Czorn
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XVIII List of Contributors Henryk M
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XX List of Contributors Józef Wron
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2 Design of Object Detection, Recog
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4 A. Babiarz et al. 1 Introduction
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6 A. Babiarz et al. The description
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344 Conclusions Control algorithms
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[Studies in Computational Intelligence 481] Artur Babiarz, Robert Bieda, Karol Jędrasiak, Aleksander Nawrat (auth.), Aleksander Nawrat, Zygmunt Kuś (eds.) - Vision Based Systemsfor UAV Applications (2013, Sprin

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