Development of a Global Vision Soccer Robot System
Date Issued
2005
Date
2005
Author(s)
Wu, Yen-Hsun
DOI
en-US
Abstract
Wide range of technologies are integrated, developed and implemented in the global vision soccer robot system. This thesis is involved in three of them: Color object recognition and tracking, wheeled mobile robot control, and multi-agent collaboration. The task of global vision module is to extract meaningful data for strategy decision module. These data are reliable and accurate for efficient tactics planning. Robust color classification plays a dramatic role for color-based image analysis. In addition, appropriate color classification reduces computational time and improves reliability by eliminating uninterested background information. Principal Component Analysis (PCA) is adopted to seek for a color space in which a color classification model is constructed straightforward. According to this model, slight color variation is robustly classified. Based on extracted data, the decision-making module estimates the field condition, and then plans strategies to collaborate agents. Role assignment enormously affects the efficiency of plan achievement. A bottom-up strategy generation mechanism simplifies the procedure to create strategies for highly dynamical environment. Dynamic feedback linearization control is adopted for the mobile robot’s motion control. The performance is good enough for robot to dribble the ball and score goal. The entire system has been completely implemented, and won the first place of 2004 National Competition of Soccer Robots.
Subjects
全域視覺
色彩分類
足球機器人
Global vision
Color classification
Soccer robot
Type
thesis
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