Abstract
This paper presents a new routing algorithm based on Lee’s algorithm. The latter was developed with view to designing printed circuit boards (PCB). It can also be adapted for seeking collisionless routes for unmanned vehicles moving in an unknown environment. Such routes need to be updated on-the-fly, taking into account changes in the environment, e.g. moving obstacles, newly detected objects. The proposed algorithm uses results from the calculations carried out in the previous steps. Hence, computations in the following steps are only required for the areas that were subject to change. Tests showed that the presented route replanner is, on average, twice as fast as Lee’s algorithm.
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References
Lee, C.Y.: An algorithm for path connection and its applications. IRE Trans. on Electronic Computers EC-10(3), 346–365 (1961)
Polańczyk, M., Owczarek, A., Strzelecki, M., Ślot, K.: Stereovision-Based Obstacle Avoidance Procedure for Autonomous Mobile Platforms. In: Corchado, E., Kurzyński, M., Woźniak, M. (eds.) HAIS 2011, Part I. LNCS, vol. 6678, pp. 206–213. Springer, Heidelberg (2011)
Corchado, E., Abraham, A.: André Carlos Ponce Leon Ferreira de Carvalho: Hybrid intelligent algorithms and applications. Information Science 180(14), 2633–2634 (2010)
Abraham, A., Corchado, E., Corchado, J.M.: Hybrid learning machines. Neurocomputing 72(13-15), 2729–2730 (2009)
Latombe, J.-C.: Robot Motion Planning. Kluwer Academic Publishers, Boston (1991)
Manikas, T.W., Ashenayi, K., Wainwright, R.L.: Generic Algorithms for Autonomous robot Navigation. IEEE Instrumenation & Measurement Magazine, 27–31 (December 2007)
Du, X., Chen, H.-H., Gu, W.-K.: Neural network and genetic algorithm based global path planning in a static environment. Journal of Zhejiang Univeristy Science 6, 549–554 (2005)
Hart, P., Nilsson, N., Rafael, B.: A formal basis for the heuristic determination of minimum cost paths. IEEE Transactions on Systems Science and Cybernetics 4, 100–107 (1968)
Koenig, S., Likhachev, M., Furcy, D.: Lifelong Planning A*. Artificial Intelligence Journal 155(1-2), 93–146 (2004)
Stentz, A.: Optimal and efficient path planning for partially-known environment. In: Proc. Int. Conf. on Robotics and Automation, vol. 4, pp. 3310–3317 (1994)
Koenig, S., Likhachev, M.: D* Lite. In: Proc. of the AAAI Conference of Artificial Intelligence (AAAI), pp. 476–483 (2002)
Lebedev, D.V., Steil, J.J., Ritter, H.J.: The dynamic wave expansion neural network model for robot motion planning in time varying environments, vol. 18, pp. 267–285. Elsevier Science Ltd. (2005)
Li, H., Yang, S.X., Biletskiy, Y.: Neural network based path planning for a multi-robot system with moving obstacles. Automation Science and Engineering, 163–168 (2008)
Kroumov, V., Yu, J.: Neural Networks Based Path Planning and Navigation of Mobile Robots. Recent Advances in Mobile Robotics (2011)
Strzelecki, M., Materka, A., Drozdz, J., Krzeminska-Pakula, M., Kasprzak, J.D.: Classification and segmentation of intracardiac masses in cardiac tumor echocardiograms. Computerized Medical Imaging and Graphics 30(2), 95–107 (2006)
BumbleBee2, http://www.ptgrey.com/products/bumblebee2/index.asp
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Polańczyk, M., Barański, P., Strzelecki, M., Ślot, K. (2012). Lee Path Replanner for Partially-Known Environments . In: Corchado, E., Snášel, V., Abraham, A., Woźniak, M., Graña, M., Cho, SB. (eds) Hybrid Artificial Intelligent Systems. HAIS 2012. Lecture Notes in Computer Science(), vol 7208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28942-2_30
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DOI: https://doi.org/10.1007/978-3-642-28942-2_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28941-5
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