Design of a Behavior-Fusion Controller
 for Mobile Robot Navigation

                                        Student:Jean-Yuan Lin

                                        Advisor:Dr. Kai-Tai Song                         


The thesis presents a design of behavior-fusion architecture for mobile robot navigation. We first design three behaviors for robot navigation, including obstacle avoidance, wall following, and goal seeking using fuzzy-logic control approach. Then, the fusion weight of each behavior is determined by using the proposed behavior-fusion neural network. The neural network maps the current environment sensor data to suitable fusion weights. Both computer simulation and practical experiments verify the effectiveness of the method.