Mobile target tracking using hierarchical grey-fuzzy motion decision-making method

This paper presents a hierarchical grey-fuzzy motion decision-making (HGFMD) algorithm, which is capable of integrating multiple sequential data for decision making and for the design of the control kernel of the target tracking system. The algorithm combines multiple grey prediction modules, each of them can online estimate the suitable model from sequential sensory information to approximate the observed dynamic system model for future-trend prediction, and for decision making through a multilayered fuzzy logic inference engine. We designed the HGFMD controller for target tracking system and implemented in our autonomous mobile robot. The HGFMD is compared with the conventional fuzzy logic controller, multilayered fuzzy controller, and the original grey-fuzzy controller we have developed previously in various target-tracking experiments. The results obtained show the high reliability of the HGFMD controller and tracking system