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Precise Long Passing Skill on Middle Size League Robot Soccer ERSOW Using Teammate Detection and Pivot Motion

Rohman Aditiya, Mochamad Mobed Bachtiar, Iwan Kurnianto Wibowo, Dana Yoga Setya Ikhwandi, Febrian Tirto Wicaksono, Septian Bagus Jumantoro

发表年份
2024
引用次数
3

摘要

The ERSOW robot, a competitor in robot soccer leagues, struggles with its current long-distance passing technique. This method, reliant on robot localization to feed robot orientation adjustments, suffers from accumulating odometry errors and unintended deviations in the ball's trajectory. This research proposes a novel approach to optimize the ERSOW robot's long-distance passing skills, addressing these limitations. The proposed solution incorporates two key elements: ball pivoting movements and a vision system. Ball pivoting maneuvers enable the robot to maintain control of the ball's position during orientation adjustments, minimizing deviations caused by robot movement. Additionally, the integration of a vision system allows the robot to continuously track the receiving teammate's location in real-time. This real-time information enables adjustments to the passing trajectory, mitigating the negative effects of odometry errors. The effectiveness of the proposed approach was evaluated through experimentation. The results demonstrate a success rate of 100% for kickoff passes with an average completion time of 1.21 seconds at a distance of 400 cm and 95.83% for corner passes with an average completion time of 2.44 seconds at a distance of 600 cm. This suggests that 600 cm is the optimal passing distance for achieving successful long passes.

关键词

LeagueComputer scienceMotion (physics)RobotArtificial intelligenceComputer visionPhysics

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