Changwon Kim and Reza Langari
Biologically inspired robots, learning and adaptive systems, fuzzy clustering
In this paper, a Brain Limbic System (BLS)-based control algorithm is used to address the problem of stationary and moving target tracking in mobile robotics. The mechanism of brain emotional learning is studied and the mathematical description of this approach in the form of BLS-based control is presented. The control strategy is driven by sensory input signal and emotional cue, and it uses these to generate appropriate velocity profile for the mobile robot to track its targets. In addition, fuzzy clustering of the error and velocity pairs is proposed to improve the performance of the BLS-based control strategy. Finally, the simulation results illustrate the characteristics of the proposed control methods in view of the target’s mobility.
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