Abstract
Path planning problem revolves around finding a path from start node to goal node without any collisions. This paper presents an improved version of Focused Wave Front Algorithm for mobile robot path planning in static 2D environment. Existing wave expansion algorithms either provide speed or optimality. We try to counter this problem by preventing the full expansion of the wave and expanding specific nodes such that optimality is retained. Our proposed algorithm ‘Optimally Focused Wave Front algorithm’ provides a very attractive package of speed and optimality. It allocates weight and cost to each node but it defines cost in a different fashion and employs diagonal distance instead of Euclidean distance. Finally, we compared our proposed algorithm with existing Wave Front Algorithms. We found that our proposed approach gave optimal results when compared with Focused Wave Front Algorithm and faster results when compared with Modified Wave Front Algorithm.
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References
Nooraliei, A., Nooraliei, H.: Path planning using wave front’s improvement methods. In: International Conference on Computer Technology and Development, ICCTD’09, IEEE, vol. 1, pp. 259–264 (2009)
Pal, A., Tiwari, R., Shukla, A.: A focused wave front algorithm for mobile robot path planning. In: Hybrid Artificial Intelligent Systems, pp. 190–197. Springer, Heidelberg (2011)
Liu, G., et al.: The ant algorithm for solving robot path planning problem. In: Third International Conference on Information Technology and Applications (ICITA), pp. 25–27 (2005)
Ganeshmurthy, M.S., Suresh, G.R.: Path planning algorithm for autonomous mobile robot in dynamic environment. In: 3rd International Conference on Signal Processing, Communication and Networking (ICSCN), IEEE, pp. 1–6 (2015)
Oh, J.S., Choi, Y.H., Park, J.B., Zheng, Y.F.: Complete coverage navigation of cleaning robots using triangular-cell-based map. IEEE Trans. Ind. Electron. 51(3), 718–726 (2004)
Zelek, J.S.: Dynamic path planning. In: IEEE International Conference on Systems, Man and Cybernetics, 1995. Intelligent Systems for the 21st Century, vol. 2, pp. 1285–1290 (1995)
Biggs, G., et al.: All the robots merely players: history of player and stage software. IEEE Robot. Autom. Mag. 20(3), 82–90 (2013)
Player/Stage Source Forge Homepage, http://playerstage.sourceforge.net10
Guo, X.: Coverage rolling path planning of unknown environments with dynamic heuristic searching. In: 2009 WRI World Congress on Computer Science and Information Engineering, IEEE, vol. 5, pp. 261–265 (2009)
Manikas, W., Ashenayi, K., Wainwright, R.: Genetic algorithms for autonomous robot navigation. IEEE Instrum. Meas. Mag. 10(6), 26–31 (2007)
Du, X., Chen, H.-H., Gu, W.-K.: Neural network and genetic algorithm based global path planning in a static environment. J. Zhejiang Univ. Sci. 6, 549–554 (2005)
Behnke, S.: Local multiresolution path planning. Preliminary version. In: Proceedings of 7th RoboCup International Symposium, Padua, Italy, pp. 332–343 (2003)
Diagonal Distance, http://theory.stanford.edu/~amitp/GameProgramming/Heuristics.html# diagonal-distance
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Ghai, B., Shukla, A. (2016). Wave Front Method Based Path Planning Algorithm for Mobile Robots. In: Satapathy, S., Das, S. (eds) Proceedings of First International Conference on Information and Communication Technology for Intelligent Systems: Volume 2. Smart Innovation, Systems and Technologies, vol 51. Springer, Cham. https://doi.org/10.1007/978-3-319-30927-9_28
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DOI: https://doi.org/10.1007/978-3-319-30927-9_28
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