Design of Localization System Based on Particle Filter Algorithm for Mobile Soccer Robot Using Encoders, Compass, and Omnidirectional Vision Sensor

Abstract

Self-localization is the basis to navigate robot or vehicle in dynamic environment such as for motion planning and obstacles avoidance. Self-localization can be divided into two categories: Local Localization-System (LLS) and Global Localization-System (GLS). Local Localization-System uses inertial sensors such as encoders which leads inevitably to the unbounded accumulation of errors. Whereas Global LocalizationSystem utilizes information based on absolute sensors so that it has a long sample time. In the Middle Size Soccer Robots, the sensors must be mounted on the robot so that it is difficult to obtain a global position directly. The particle filter algorithm is designed as a technique for combining both inertial and absolute sensor data to overcome the problems of Local Localization-System and Global Localization-System on mobile soccer robot. In this paper, three encoders are used to provide odometry motion model, an omnidirectional vision sensor is used to give weight to the particles, and ambiguity problems is overcome by using an electronic compass. The result of this test show that localization by using Particle Filter Algorithm gives better performance than Local Localization-System and can overcome the Global LocalizationProblems.