Intelligent Control of a Mobile Robot for Service Use in Office Buildings and Its Soft Computing Algorithms

Abstract

The arrangement principles and design methodology on soft computing for complex control framework of AI control system are introduced. The basis of this methodology is computer simulation of dynamics for mechanical robotic system with the help of qualitative physics and search for possible solutions by genetic algorithms (GA). On fuzzy neural network (FNN) optimal solutions for navigation with avoidance of obstacles and technological operations as opening of door with a manipulator are obtained and knowledge base (KB) for fuzzy controller is formed. Fuzzy qualitative simulation, GA and hierarchical node map (HN), and FNN have demonstrated their effectiveness for path planning of a mobile robot for service use. New approach for direct human-robot communication with natural language and cognitive graphics is introduced. The results of fuzzy robot control simulation, monitoring, and experimental investigations are presented.