Self-Localization of Humanoid Robot in a Soccer Field

Abstract

RoboCup is an annual international robotics competition that encourages the research and development of artificial intelligence and robotics. This thesis presents the algorithm developed for self-localization of small-size humanoid robots, RO-PE (RObot for Personal Entertainment) series, which participate in RoboCup Soccer Humanoid League (Kid-Size).

Localization is the most fundamental problem to providing a mobile robot with autonomous capabilities. The problem of robot localization has been studied by many researchers in the past decades. In recent years, many researchers adopt the particle filter algorithm for localization problem.

In this thesis, we implement the particle filter on our humanoid robot to achieve self-localization. The algorithm is optimized for our system. We use robot kinematic to develop the motion model. The vision model is also built based on the physical characteristics of the onboard camera. We simulate the particle filter algorithm in MatLab? to validate the effectiveness of the algorithm and develop a new switching particle filter algorithm to perform the localization. To further illustrate the effectiveness of the algorithm, we implement the algorithm on our robot to realize self-positioning capability.