This paper presents a new brain-inspired, switching control approach for a car-like autonomous vehicle using a basal ganglia (BG) model as an action selection mechanism. The problem domain has challenging nonholonomic and state constraints which imply no single stabilizing controller solution is possible by time-invariant smooth state feedback. To allow the BG make the correct controller selection from a family of candidate motion controllers, a fuzzy logic-based salience model using reference and tracking error only is developed, and applied in a soft switching control mechanism. To demonstrate the effectiveness of our approach for motion tracking control, we show effective control for a circular trajectory tracking application. The performance and advantages of the proposed fuzzy salience model and the BG-based soft switching control scheme against a traditional single control method are compared. © 2013 Springer-Verlag.
CITATION STYLE
Yang, E., Hussain, A., & Gurney, K. (2013). A basal ganglia inspired soft switching approach to the motion control of a car-like autonomous vehicle. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7888 LNAI, pp. 245–254). https://doi.org/10.1007/978-3-642-38786-9_28
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