Soft computing algorithms for intelligent control of a mobile robot for service use

Abstract

 The arrangement principles and design methodology on soft computing for complex control framework of AI control system in Part 1 of this paper are developed. 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). In Part 2 optimal solutions for navigation with avoidance of obstacles and technological operations as opening of door with a manipulator on GA and fuzzy neural network (FNN) 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. The results of fuzzy robot control simulation, monitoring, and experimental investigations are described.