Abstract
This paper studies a simplified pursuit-evasion problem. We assume that the evader moves with constant speed along a trajectory that is well-defined and known a priori. The objective of steering control of the pursuer modeled as a nonholonomic unicycle-type mobile robot is to intercept the moving evader. An adaptive learning approach of fuzzy logic controller is developed as an inverse kinematics solver of unicycle to enable a mobile robot to use the evader trajectory to adapt its control actions to pursuit-evasion game. In this proposed approach, GA evolves the parameter values of the fuzzy logic control system aiming to approximate the inverse kinematics of pursuer so as to generate a trajectory capturing the evader. Simulation results of pursuit-evasion game illustrate the performance of the proposed approach.
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Chung, HC., Liu, JS. (2010). Adaptive Learning Approach of Fuzzy Logic Controller with Evolution for Pursuit–Evasion Games. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2010. Lecture Notes in Computer Science(), vol 6421. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16693-8_49
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DOI: https://doi.org/10.1007/978-3-642-16693-8_49
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