Mobile Robot Navigation in an Unstructured and Unknown Environment Using AI Techniques

This paper shows the new approach to solve the Mobile Robot Navigation issues. The approach consists of the simple behavior design based on Situation Context of Applicability (SCA) and arbitration of the concurrent act ivies of several possible competing behaviors. This work also shows some of the reviews of the related approaches, which are attempted to resolve the robot navigational issues. In this work the design of the behavior is based on regulatory control using fuzzy logic and the coordination and behavior selection is defined by fuzzy rules, which uses the SCA for each behavior. Also, in the SCA method, the decision-making processes of a few behaviors have been developed and applied for Active Media Pioneer Robot. Fuzzy Logic Decision Mechanism (FLDM) is developed by using the Fuzzy Associate Membership process, which are used here simplifies the design of the robotic controller and reduces the number of rules to be determined. In addition, any behavior can be added or modified easily. Applying the proposed methods, experimental results are also shown for the Obstacle avoidance, Wall following and Seek-goal behaviors.