Self-localization Method of Omni-directional Soccer Robot Based on Quantum Immune Algorithm

Abstract

In order to more effectively solve self-localization problem for soccer robot, this paper introduces a selflocalization method that is an optimization algorithm based on Quantum Immune Algorithm (QIA). A type of quantum algorithm encoding form is used which is the Bloch spherical coordinate encoding form. It can both guarantee the diversity of initial population. The immune operation can reduce the probability that the QIA gets local optimal solution. This algorithm is combined with white line localization method, and by means of the feature point matching method finally determines the robot’s pose in the field. Simulation experiments and contrasts in Xi’an University of Science and Technology of soccer robot lab show that this method not only improves the global localization accuracy of the mobile robot, but also enhances its real-time. The actual application performance test can verify the feasibility and stability of this self-localization method. In 2011 and 2012, we all ranked the first place RoboCup middle-sized soccer robot league in Educational Robot Competition in China. The Educational Robot Competition is one of the China major robotic event. These prizes indicate that the QIA combined with white line method has superiority in solving the self-localization problem for soccer robot.