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In this paper, we investigate the use of adaptive techniques in the optimization of navigation of Khepera mobile robot in an unstructured and dynamic environment. We optimize the performance of our simplified fuzzy controller using neural network that utilizes genetic algorithm learning. The adaptation of the system involves the tuning of the control rules thereby trimming the control actions, and adjusting the fuzzy controller output gain. We realised an improved performance in our adaptivedoi:10.15837/ijccc.2012.1.1429 fatcat:33ciz3y5azcfjfjfc2ne2bwdqu