Autonomous Navigation of AMR Based on Adaptive Hierarchical Fuzzy Motion Control

Autonomous Navigation of AMR Based on Adaptive Hierarchical Fuzzy Motion Control

In this paper, we present a navigation algorithm that allows an AI vision robot to intelligently find its goal in unknown, dynamic environments using a vision sensor. Instead of relying on the "sensor fusion" approach, which generates a trajectory based on an environmental model and sensory data, our method uses "command fusion" to guide the robot's movements. The navigation strategy incorporates fuzzy rules designed to optimize both goal acquisition and obstacle avoidance. To interpret the virtual environment by obstacle avoidance, we apply a command fusion technique that combines sensory data from both ultrasonic and vision sensors. Overall, our approach demonstrates that command fusion, combined with fuzzy logic, offers a robust and flexible solution for autonomous navigation in challenging environments. The experimental results show that the robot is capable of efficiently reaching its goal while successfully avoiding obstacles, highlighting the effectiveness of the proposed algorithm.