Abstract

This paper proposes a hierarchical control architecture to deal with the Trajectory Tracking Problem while an autonomous omnidirectional wheeled mobile robot operates. A traditional velocity controller and an intelligent decision-making neural network controller address the problem, considering the robot’s kinematic and dynamic models. A neuroevolution technique evolves a smart Neurocontroller functionally attached to a Resolved Acceleration PI/PD Controller. The resulting control strategy shows to improve trajectory tracking errors during simulation studies.

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