Intelligent Robotic Systems: Design, Planning and Control
W. Jacak - Intelligent Robotic Systems: Design, Planning and Control - Kluwer Academic Publisher, 1999, pp. 1-320
Robotic system is an effective tool for automation necessary for modernization, international competitiveness in several industrial branches and economic integration. Any increase in productivity, flexibility, and the continuous assurance of high quality is losely related to the level of intelligence and autonomy of the robots and the robotic systems. A robotic system that recognizes the environment and executes the commanded tasks is developed to achieve more dexterous tasks in a more complicated environment. Integration of sensory data and the building up an internal model of environment, action planning based on this model and learning based control of action are the current topics in this area. The system integration is one of the most difficult tasks whereby sensors, vision systems, controllers, machine elements, software for planning, supervision, and learning are tied together to a functional entity. Moreover, robot intelligence should interact with dynamic worlds. Cognition, perception, action, and learning are all essential components of such systems and their integration into real systems of different levels of complexity should help to clarify the nature of robotic intelligence. In a complex robotic agent system, the knowledge about surrounding environment determines the structure and methodologies used to control and coordination the system, which lead to an increase the intelligence of individual system components.This book will only treat the intelligent robotic cell and its components. The fully autonomous robotic multiagent system is not covered here. However, the on-line components and algorithms of an intelligent robotic cell can be used in multiagent systems as well The book deals with the basic research issues associated with each subsystem of the intelligent robotic cell and discuss how different Discrete System Theory, Artificial Intelligence, Fuzzy Set Theory and Neural Network tools and methods can address these issues. Each unit of work cell control synthesis system need different mathematical and system engineering tools such as graph searching, optimisation, neural computing, fuzzy decision making, simulation of discrete dynamic system, and event based system methods.
The material in the book has been divided into two parts. The first part of the book gives a detailed formal descriptions and solutions of the technological process and robots motions planning problems. The presented here methods are used in off-line phase of synthesis of the intelligent robotic system. The sections present consequently the methods and algorithms which can be used to obtain the executable plan of robots motions and manipulations based only on general description of the technological task or on the final state of assembly process. The second part presents the real time event based multilevel coordination and control system of robotic system. The components of this control system use the discrete event, neural network, and fuzzy logic based controllers. Depending on the knowledge state about the surrounding environment of robotic agent the different planning, coordination and control methods are described. These methods need different autonomy stage from a robotic agent. The sections present the possible solutions to obtain the required intelligence behaviour of robotic system. In writing this book, a formal approach has been adopted. The usage of mathematics is limited to the level required to maintain the clarity of the presentation. The book should contribute to better understanding, advancement, and developed of new applications of intelligent robotic systems.