Abstract
This article presents an A* search algorithm to be applied to path planning in a Chinese chess game, and uses multiple mobile robots to present the scenario. The mobile robots have a cylindrical shape, and their diameter, height, and weight are 8 cm, 15 cm, and 1.5 kg, respectively. The controller of the mobile robots is a MCS-51 chip. We play the Chinese chess game using multiple mobile robots according to the evaluation algorithm of the game, and calculate the displacement by the encoder of a DC servomotor. The A* search algorithm can solve the shortest-path problem for the mobile robots from the starting point to the target point on the chess board. The simulated results found the shortest path for the mobile robots (chess pieces) moving to target points from their starting points in a collision-free environment. Finally, we implemented the experimental results on a Chinese chess board using mobile robots. Users can play the Chinese chess game using the supervising computer via a wireless RF interface. The scenario of the feedback of the Chinese chess game to the user interface uses an image system.
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References
Yen SJ, Chen JC, Yang TN, et al (2004) Computer Chinese chess. ICGA J 27(1):3–18
Darwen P, Yao X (2002) Co-evolution in the iterated prisoner’s dilemma with intermediate levels of cooperation: application to missile defense. Int J Comput Intell Appl 2(1):83–107
Yong CH, Miikkulainen R (2001) Cooperative co-evolution of multi-agent systems. University of Texas, Austin, Tech. Rep. AI01-287
Ong CS, Quek HY, Tan KC, et al (2007) Discovering Chinese Chess strategies through co-evolutionary approaches. IEEE Symposium on Computational Intelligence and Games, pp 360–367
Wang J, Luo YH, Qiu DN, et al (2005) Adaptive genetic algorithm’s implement on evaluation function in computer Chinese chess. Proceeding of ISCIT, pp 1206–1209
Lee WP, Liu LJ, Chiou JA (2006) A component-based framework to rapidly prototype online chess game for home entertainment. IEEE International Conference on System, Man and Cybernetics, pp 4011–4016
Zhou W, Zhang JL, Wang YZ (2008) The iterative sort search techniques based on percentage evaluation. Chinese Control and Decision Conference, pp 5263–5266
Su KL, Shiau SV, Guo JH, et al (2009) Mobile robot based on-line Chinese chess game. 4th International Conference on Innovative Computing, Information and Control, p 63
Saber Y, Senjyu T (2007) Memory-bounded ant colony optimization with dynamic programming and A* local search for generator planning. IEEE Trans Power Syst 22(4):1965–1973
Chia SH, Su KL, Wang CC, et al (2010) Multiple robot system applying in Chinese chess game. Innovative Comput Inform Control, Express Lett (ICIC-EL) 4(5B):2027–2032
Hart PE, Nilsson NJ, Raphael B (1968) A formal basis for the heuristic determination of minimum cost paths. IEEE Transactions on Systems Science and Cybernetics SSC4 4(2):100–107. 10.1109/TSSC.1968.300136
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This work was presented in part at the 16th International Symposium on Artificial Life and Robotics, Oita, Japan, January 27–29, 2011
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Su, KL., Chung, CY., Zou, JT. et al. A* search algorithm applied to a Chinese chess game. Artif Life Robotics 16, 132–136 (2011). https://doi.org/10.1007/s10015-011-0882-3
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DOI: https://doi.org/10.1007/s10015-011-0882-3