, Volume 7, Issue 1, pp 55-63
Date: 14 Feb 2010

Action control of soccer robots based on simulated human intelligence

Rent the article at a discount

Rent now

* Final gross prices may vary according to local VAT.

Get Access


A multi-modal action control approach is proposed for an autonomous soccer robot when the bottom hardware is unchangeable. Different from existing methods, the proposed control approach defines actions with the principle of “perception-planning-action” inspired by human intelligence. Character extraction is used to divide the perception input into different modes. Different control modes are built by combining different control methods for the linear velocity and angular velocity. Based on production rules, the motion control is realized by connecting different perceptions to the corresponding control mode. Simulation and real experiments are conducted with the middle-sized robot Frontier-I, and the proposed method is compared with a proportional-integral-derivative (PID) control method to display its feasibility and performance. The results show that the multi-modal action control method can make robots react rapidly in a dynamic environment.

This work was supported by National Natural Science Foundation of China (No. 60443004) and Science and Technology Project of CQ Education Committee (No.KJ080621).
Tie-Jun Li received the B. Sc. and M. Sc. degrees in automation from the Chongqing University, PRC in 2000 and 2005, respectively. In 2005, he was a faculty member at Chongqing Jinmei Communication Co., Ltd., PRC. He is currently an engineer at Jimei University, PRC.
His research interests include robotics, communication systems, and electromagnetic compatibility.
Gui-Qiang Chen received the B.Eng. degree in wireless communication from Chongqing Communication College, PRC in 2000. He received the M. Sc. degree in intelligent control and pattern recognition from Chongqing University, PRC. Now he is working with Chongqing Communication College.
His research interests include intelligent control, evolutional computation and pattern recognition.
Gui-Fang Shao received the B. Sc., M. Sc., and Ph.D. degrees from Chongqing University, PRC in 2000, 2003, and 2007, respectively, all in control theory and control engineering. She is currently an associate professor with the Institute of Pattern Recognition and Intelligence System, Xiamen University, PRC.
Her research interests include the pattern recognition, image processing, and robot control.