Machine vision and fuzzy logic-based navigation control of a goal-oriented mobile robot

This work addresses a new goal oriented navigation framework for autonomous system. In the proposed work, a hybrid control system, comprising deliberative and behavior-based architectures, has been developed. Deliberative layer employs a monocular vision camera to obtain the position of the goal while behavior-based framework makes use of the motor schema technique for safe navigation. Fuzzy logic is also adopted in order to enhance the performance of the navigation system. A rigorous series of experiments has been conducted using two navigation methods, which are the proposed control system and the conventional navigation technique utilizing the potential field method for achieving the desired goals. Both systems are implemented in the simulated experiments using Stage simulator. By employing these two approaches, it is possible to present a comparison of the navigation results between the systems utilizing different navigation techniques. The experimental results reveal that the proposed system produces better navigation performance compared to the conventional method in terms of safe and successful navigation, with a smoother trajectory and consistent motion.