TY - GEN
T1 - Multi-robot coordination strategy for 3 vs. 3 teen-sized humanoid robot soccer game
AU - Fang, Nien Chu
AU - Tsai, Ting Nan
AU - Wu, Li Fan
AU - Cheng, Chuan Han
AU - Huang, Chian Yi
AU - Liu, Chun Yuan
AU - Li, Tzuu Hseng S.
N1 - Funding Information:
ACKNOWLEDGMENT This work was supported in part by the Ministry of Science and Technology, Taiwan, ROC, under Grant MOST 104-2221-E-006-228-MY2 and in part by the Ministry of Education, Taiwan, within the Aim for the Top University Project through National Cheng Kung University, Tainan, Taiwan, R.O.C.
Publisher Copyright:
© 2017 IEEE.
PY - 2018/2/7
Y1 - 2018/2/7
N2 - This paper proposes a multi-robot coordination strategy system concerning 3 vs. 3 teen-sized humanoid robot soccer game. Three main technologies are integrated in the system, including object recognition and self-localization, and coordination strategy. Because the line, ball, and goal posts are colored white, we utilize the contour features to recognize them and calculate their positions in robot coordinate. Hence, suppose the robot position in the world coordinate is known, the position of the line, ball, and goal posts in world coordinate can be determined. We figure out the initial position of the robot and update the position by the value of the Inertial Measurement Unit (IMU) and the estimate movement distance. Every robot transmits its location and his own information to the central control player to construct a global map used to generate a suitable strategy and to assign roles. A simulation software is constructed in this paper. After that, experiments show the strategy is effective on humanoid robots. These results illustrate the efficiency of the proposed coordination strategy.
AB - This paper proposes a multi-robot coordination strategy system concerning 3 vs. 3 teen-sized humanoid robot soccer game. Three main technologies are integrated in the system, including object recognition and self-localization, and coordination strategy. Because the line, ball, and goal posts are colored white, we utilize the contour features to recognize them and calculate their positions in robot coordinate. Hence, suppose the robot position in the world coordinate is known, the position of the line, ball, and goal posts in world coordinate can be determined. We figure out the initial position of the robot and update the position by the value of the Inertial Measurement Unit (IMU) and the estimate movement distance. Every robot transmits its location and his own information to the central control player to construct a global map used to generate a suitable strategy and to assign roles. A simulation software is constructed in this paper. After that, experiments show the strategy is effective on humanoid robots. These results illustrate the efficiency of the proposed coordination strategy.
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U2 - 10.1109/CACS.2017.8284265
DO - 10.1109/CACS.2017.8284265
M3 - Conference contribution
AN - SCOPUS:85050500313
T3 - 2017 International Automatic Control Conference, CACS 2017
SP - 1
EP - 6
BT - 2017 International Automatic Control Conference, CACS 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 International Automatic Control Conference, CACS 2017
Y2 - 12 November 2017 through 15 November 2017
ER -