Study And Experiment Of Real-time Control And Strategies Planning For Small-size Soccer Robot Systems

The development of collaborative multi-robot systems is multi-disciplinary, involving computer science, communication, control theory, intelligent robots, multi-sensor technology, information fusion, computer vision, bionics, artificial intelligence, etc. Today, the number of scholars and researchers who study collaborative multi-robot systems is increasing rapidly. The research level and scope of collaborative multi-robot systems are also continuously increasing.In this thesis, small-size robot soccer competition has been as a research platform to conduct the fundamental research, simulation verification and practice competition of a collaborative multi-robot system.The major contributions of the thesis include:1. The computation verb theory is combined with the region reconnaissance method to solve the difficulty associated with real-time image acquisition in the small-size soccer robot system. Through matching robot marks, resolving similarity, and decomposing computation verb into a'low verb'and a'column verb', the real-time system computation, as well as the accuracy and stability of image information acquisition under the non-uniform illumination condition are greatly improved, laid a solid foundation for path planning research.2. Based on the study of motion trajectory of small size soccer competition, the Delaunay triangle grid is used to optimise path scheduling. The key points and their simplified postures are adopted to optimize the robot path so that the small-size robots are able to plan their paths with a high degree of system stability and fast speeds.3. The Extended Kalman-Bucy Filter and the RPF neural network are used in small-size soccer robots and their position prediction so that the complexity of modelling small size soccer robots is greatly reduced. Through the pre-collected input and output data, motion trajectories of small size soccer robots are predicted. This provides an important foundation of path planning and system decision of small size soccer robots.4. The Monte-Carlo theory is applied to the small-size robot soccer system to study its reinforcement learning, including the overall strategy learning and the individual ability learning. As a result, it has realized many small soccer robot dynamic role assignments, avoided the movement mutual conflict, and obtained the good coordinate effect.5. Data fusion theory is investigated to solve many practical problems, such as The straight line adjusts, the movement evades bonds, the movement accuracy judgment, the intelligent judgment of"injured player"in the multi-robot system comprehensively based on the foundation of the multi-sensor system.The research results in this thesis have applied to the small-size robot system of Shanghai University, including many laboratory experiments, participations of many domestic and international robot-soccer competitions. The team continuous entered top 4 in 2004-2007 RoboCup China, became the league champion in 2007 RoboCup Iran Open, as well as the league champion in 2008 RoboCup Iran Open.