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Modeling and implementation of a fully autonomous soccer robot based on omni‐directional vision system
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PurposeThe purpose of this paper is to design and implement a team of middle size soccer robots to conform RoboCup middle‐size league.Design/methodology/approachFirst, according to the rules of RoboCup, a middle size soccer robot was designed. The proposed autonomous soccer robot consists of the mechanical platform, motion control module, omni‐directional vision module, front vision module, image processing and recognition module, investigated target object positioning and real coordinate reconstruction, robot path planning, competition strategies, and obstacle avoidance. This soccer robot equips the laptop computer system and interface circuits to make decisions.FindingsIn fact, the omni‐directional vision sensor of the vision system deals with the image processing and positioning for obstacle avoidance and target tracking. The boundary‐following algorithm is applied to find the important features of the field. The sensor data fusion method is utilized in the control system parameters, self‐localization, and world modeling. A vision‐based self‐localization, and the conventional odometry systems are fused for robust self‐localization. The localization algorithm includes filtering, sharing, and integration of the data for different types of objects recognized in the environment.Originality/valueThis paper presents results of research work in the field of autonomous robot‐middle size soccer robot supported by IAU‐Khorasgan Branch (Isfahan).
Title: Modeling and implementation of a fully autonomous soccer robot based on omni‐directional vision system
Description:
PurposeThe purpose of this paper is to design and implement a team of middle size soccer robots to conform RoboCup middle‐size league.
Design/methodology/approachFirst, according to the rules of RoboCup, a middle size soccer robot was designed.
The proposed autonomous soccer robot consists of the mechanical platform, motion control module, omni‐directional vision module, front vision module, image processing and recognition module, investigated target object positioning and real coordinate reconstruction, robot path planning, competition strategies, and obstacle avoidance.
This soccer robot equips the laptop computer system and interface circuits to make decisions.
FindingsIn fact, the omni‐directional vision sensor of the vision system deals with the image processing and positioning for obstacle avoidance and target tracking.
The boundary‐following algorithm is applied to find the important features of the field.
The sensor data fusion method is utilized in the control system parameters, self‐localization, and world modeling.
A vision‐based self‐localization, and the conventional odometry systems are fused for robust self‐localization.
The localization algorithm includes filtering, sharing, and integration of the data for different types of objects recognized in the environment.
Originality/valueThis paper presents results of research work in the field of autonomous robot‐middle size soccer robot supported by IAU‐Khorasgan Branch (Isfahan).
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