Abstract
Collision detection is very important to improve the truth and immersion in the virtual environment. Firstly the paper analyzes the problems that exist in traditional algorithms. There is no algorithm suitable to every situation, and the more complex the situations are, the more rapidly the efficiency declines. Secondly the paper analyses the problem of collision detection in theory, and then converts the problem of the collision detection to the non-linear programming problem with restricted conditions. In this paper, the definition of the distance between two objects and for which the quantum coding is given. Through the steps, such as quantum clone, quantum variation, the problem of collision detection is solved. Finally, the simulation test shows that the quantum-inspired immune algorithm has much more effective impact on solving the extreme-value problem compared to the traditional genetic algorithm. It is feasible to use the algorithm in collision detection.
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Wu, J., Peng, L., Chen, L., Yang, L. (2010). Quantum Immune Algorithm and Its Application in Collision Detection. In: Li, K., Fei, M., Jia, L., Irwin, G.W. (eds) Life System Modeling and Intelligent Computing. ICSEE LSMS 2010 2010. Lecture Notes in Computer Science, vol 6329. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15597-0_16
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DOI: https://doi.org/10.1007/978-3-642-15597-0_16
Publisher Name: Springer, Berlin, Heidelberg
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