Abstract
This paper presents a framework for robot path planning based on the A* search algorithm in the presence of dynamically expanding obstacles. The overall method follows Cellular Automata (CA) based rules, exploiting the discrete nature of CAs for both obstacle and robot state spaces. For the search strategy, the discrete properties of the A* algorithm were utilized, allowing a seamless merging of both CA and A* theories. The proposed algorithm guarantees both a collision free and a cost efficient path to target with optimal computational cost. More particular, it expands the map state space with respect to time using adaptive time intervals in order to predict the necessary future expansion of obstacles for assuring both a safe and a minimum cost path. The proposed method can be considered as being a general framework in the sense that it can be applied to any arbitrary shaped obstacle.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Pradalier, C., Hermosillo, J., Koike, C., Braillon, C., Bessiere, P., Laugier, C.: The CyCab: a car-like robot navigating autonomously and safely among pedestrians. Robotics and Autonomoys Systems 50(1), 51–68 (2005)
Balaguer, C., Gimenez, A., Huete, A.J., Sabatini, A.M., Topping, M., Bolmsjo, G.: The MATS robot: service climbing robot for personal assistance. IEEE Robotics & Automation Magazine 13, 51–58 (2006)
Kyriakoulis, N., Gasteratos, A., Amanatiadis, A.: Comparison of data fusion techniques for robot navigation. In: Advances in Artificial Intelligence, pp. 547–550 (2006)
Baohua, J., Liang, Z.: A Path Planning Method of Contingency Logistics Based on Max-Min Ant System. In: Proceedings of the 2010 Asia-Pacific Conference on Wearable Computing Systems, pp. 311–314 (2010)
Chien, S., Wang, H., Lewis, M.: Human vs. algorithmic path planning for search and rescue by robot teams. In: 54th Annual Meeting of the Human Factors and Ergonomics Society, pp. 379–383 (2011)
Hwang, Y., Ahuja, N.: Gross motion planning –A survey. ACM Comput. Surv. 24, 219–291 (1992)
Rao, N.S.V.: An algorithmic framework for navigation in unknown terrains. IEEE Trans. Comput., 37–43 (1989)
Sugihara, K.: An approximation of generalized Voronoi diagrams by ordinary Voronoi diagrams. Graphical Models and Image Processing 55, 522–531 (1993)
Tzionas, P.G., Thanailakis, A., Tsalides, P.G.: Collision-Free Path planning for a Diamond-Shaped Robot Using Two-Dimensional Cellular Automata. IEEE Robotics & Automation Magazine 13, 237–250 (1997)
Wang, C., Soh, Y.C., Wang, H., Wang, H.: A hierarchical genetic algorithm for path planning in a static enviroment with obstacles. In: Canadian Conference on Electrical and Computer Engineering, IEEE CCECE 2002, vol. 3, pp. 1652–1657 (2002)
Noborio, H., Naniwa, T., Arimoto, S.: A feasible motion planning algorithm for a mobile robot an a quadtree representation. In: Proc. IEEE Int. Conf. Robot. Automat., pp. 237–332 (1989)
Jahabin, M.R., Fallside, F.: Path planning using a wave simulation technique in the configuration space. In: Gero, J.S. (ed.) Artificial Intelligence in Engineering: Robotics and Processes. Computational Mechanics Publications, Southhampton (1988)
Zelinsky, A.: Using path transforms to guide the search for findpath in 2D. Int. J. Robot., 315–325 (1994)
Aleksander, I., Hanna, F.K.: Automata Theory: An engineerinng Approach. Crane Russak, New York (1975)
Gray, L.: A Mathematician Looks at Wolfram’s New Kind of Science. Not. Amer. Math., 200–211 (2003)
Hart, P.E., Nilsson, N.J., Raphael, B.: A Formal Basis for the Heuristic Determination of Minimum cost paths. IEEE Trans. on Systems Science and Cybernetics, SSC 2004, pp. 100–107 (2004)
Dehter, R., Judea, P.: Generalized best-first search strategies and the optimality of A*. Journal of the ACM, 505–536
Pearl, J.: Heuristics: Intelligent Search Strategies for Computer Problem Solving. Addison-Wesley
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Charalampous, K., Amanatiadis, A., Gasteratos, A. (2012). Efficient Robot Path Planning in the Presence of Dynamically Expanding Obstacles. In: Sirakoulis, G.C., Bandini, S. (eds) Cellular Automata. ACRI 2012. Lecture Notes in Computer Science, vol 7495. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33350-7_34
Download citation
DOI: https://doi.org/10.1007/978-3-642-33350-7_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33349-1
Online ISBN: 978-3-642-33350-7
eBook Packages: Computer ScienceComputer Science (R0)