Abstract
problem of Offline Point-to-Point Autonomous Mobile Robot Path Planning. The problem consist of generating “valid” paths or trajectories, for an Holonomic Robot to use to move from a starting position to a destination across a flat map of a terrain, represented by a two dimensional grid, with obstacles and dangerous ground that the Robot must evade. This means that the GA optimizes possible paths based on two criteria: length and difficulty. This paper describes the use of a Genetic Algorithm (GA) for the
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Xiao, J. and Michalewicz, Z. (2000), An Evolutionary Computation Approach to Robot Planning and Navigation, in Hirota, K. and Fukuda, T. (eds.), Soft Computing in Mechatronics, Springer-Verlag, Heidelberg, Germany, 117 – 128.
Ajmal Deen Ali, M. S., Babu, N. and Varghese, K. (2002), Offline Path Planning of cooperative manipulators using Co-Evolutionary Genetic Algorithm, Proceedings of the International Symposium on Automation and Robotics in Construction, 19th (ISARC), 415–124.
Farritor, S. and Dubowsky, S. (2002), A Genetic Planning Method and its Application to Planetary Exploration, ASME Journal of Dynamic Systems, Measurement and Control, 124(4), 698–701.
Sauter, J. A., Matthews, R., Parunak, H. V. D. and Brueckner, S. (2002), Evolving Adaptive Pheromone Path Planning Mechanisms, First International Conference on Autonomous Agents and Multi-Agent Systems, Bologna, Italy, 434- 440.
Sugihara, K. (1999), Genetic Algorithms for Adaptive Planning of Path and Trajectory of a Mobile Robot in 2D Terrains, IEICE Trans. Inf. & Syst., Vol. E82-D, 309 – 313.
Sugihara, K. (1997), A Case Study on Tuning of Genetic Algorithms by Using Performance Evaluation Based on Experimental Design, Tech. Rep. ICS-TR-97–01, Dept. of Information and Computer Sciences, Univ. of Hawaii at Manoa.
Sugihara, K. (1997), Measures for Performance Evaluation of Genetic Algorithms, Proc. 3rd. joint Conference on Information Sciences, Research Triangle Park, NC, vol. I, 172–175.
Cobb, H. G. (1990), An Investigation into the Use of Hypermutation as an Adaptive Operator in Genetic Algorithms Having Continuous, Time-Dependent Nonstationary Environments, Technical Report AIC-90–001, Naval Research Laboratory, Washington, D. C.
Fonseca, C. M. and Fleming, C. J. (1993), Genetic algorithms for multiobjective optimization: formulation, discussion and generalization, 5th Int. Conf. Genetic Algorithms, 416–423.
Srinivas, M. and Deb, K. (1994), Multiobjective Optimization using Nondominated Sorting in Genetic Algorithms, Evolutionary Computation, 2(3), 221- 248.
Man, K. F., Tang, K. S. and Kwong, S. (1999), Genetic Algorithms, Ed. Springer, 1st Edition, London, UK.
Oliveira, G. M. B., Bortot, J. C. and De Oliveira, P. P. B. (2002), Multiobjective Evolutionary Search for One-Dimensional Cellular Automata in the Density Classification Task, in Proceedings of Artificial Life VIII, MIT Press, 202- 206.
Schaffer, J. D. (1985), Multiple Objective Optimization with Vector Evaluated Genetic Algorithms, Genetic Algorithms and their Applications: Proceedings of the First International Conference on Genetic Algorithms, 93–100.
Goldberg, D. E. (1989), Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley, Reading, MA.
Spandl, H. (1992), Lernverfahren zur Unterstützung der Routenplanung fur eine Mobilen Roboter, Diss. Universität Karlsruhe, auch VDI-Forsch-Heft Reihe 10 Nr. 212, Düsseldorf, Germany, VDI-Verlag.
Choset, H., La Civita, M. L. and Park, J. C. (1999), Path Planning between Two Points for a Robot Experiencing Localization Error in Known and Unknown Environments, Proceedings of the Conference on Field and Service Robotics (FSR'99), Pittsburgh, PA.
Kim, B. N., Kwon, O. S., Kim, K. J., Lee, E. H. and Hong, S. H. (1999), “A Study on Path Planning for Mobile Robot Based on Fuzzy Logic Controller”, Proceedings of IEEE TENCON'99, 1–6.
Planas, R. M., Fuertes, J. M. and Martinez, A. B. (2002), Qualitative Approach for Mobile Robot Path Planning based on Potential Field Methods, Sixteenth International Workshop on Qualitative Reasoning (QR/02), 1–7.
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Garibaldi, J., Barreras, A., Castillo, O. (2007). Intelligent Control and Planning of Autonomous Algorithms Mobile Robots Using Fuzzy Logic and Genetic. In: Castillo, O., Melin, P., Kacprzyk, J., Pedrycz, W. (eds) Hybrid Intelligent Systems. Studies in Fuzziness and Soft Computing, vol 208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-37421-3_16
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DOI: https://doi.org/10.1007/978-3-540-37421-3_16
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