全自主足球机器人的射门与守门算法研究
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摘要
足球机器人系统是一类典型的移动机器人的对抗系统,具有实时性要求高、环境高度动态、不可预测性等特点,并将高科技研究和足球联系在一起,通过足球比赛来检验各种理论、方法和技术。本文以全自主足球机器人系统为平台,主要研究了目标的识别与定位和机器人射门与守门算法。
视觉系统的目标识别与定位是全自主足球机器人系统的基础,它对机器人感知环境起着关键的作用。HIT-III型全自主机器人的视觉系统是由全维视觉系统和前向单目系统组成的双目异构视觉,两个视觉系统采用基于颜色信息的目标识别,可以独立的对目标进行识别和定位,最后利用卡尔曼滤波进行数据融合。
本文把对全自主足球机器人的射门与守门算法的研究转化为对决策系统的研究。在足球机器人系统里,决策系统的任务是将视觉系统传来的场上的数据进行分析,对场上比赛形势做出判断,形成比赛策略,并通过角色的决策模型来规划机器人的运动,完成射门与守门任务。在设计决策系统时,采用了有穷自动机的理论,并构造了各角色的有穷状态机决策模型,每个状态都对应着一个算法,用来控制机器人运动,在状态进行转换时就完成了机器人的运动与相应任务。
最后,经射门与守门实验表明,机器人运动轨迹平滑、实时性高,该决策算法可以应用在全自主足球机器人比赛中;并进一步验证了双目异构视觉系统的可行性和经过卡尔曼滤波算法融合后的定位信息的准确性。
The robot soccer system is a typical competition system of mobile robot, with the character of high request of real time, high dynamic environment, un-predictability, etc., and it associates high technology study with soccer, examining various theories, methods and techniques by the soccer game. This paper is based on autonomous soccer robot system, and the main study is object identification and localization, and shooting arithmetic and goalkeeping arithmetic.
Object identification and localization of vision system is the foundation of autonomous soccer robot system, it plays a pivotal role in apperceiving surroundings for robot. The vision system of HIT-III autonomous soccer robot is binocular heterogeneous vision, composed of omni-vision and monocular vision, each of which can identify objects based on color information and localize objects independently, and the localization data is fused by Kalman filter at last.
In this paper, studying in shooting arithmetic and goalkeeping arithmetic of autonomous soccer robot is converted into designing a decision-making system. In robot soccer system, the function of the decision-making system is that to analyze the sounding data from vision system, to estimate the state of the match, to make a decision, and to control the robot moving to complete the shooting and defense task. A deterministic finite state automaton is used in designing decision-making system, which is constructed for each role. Every state corresponds with arithmetic, which control the robot to move, so when the state is transferring in deterministic finite state automaton, the robot is working to move and complete task.
Finally, experiments showed that, this decision-making arithmetic, with the smooth trajectory of robot motion and high real time, can be used in autonomous soccer robot. And it proves the feasibility of binocular heterogeneous vision and accurately of localization data that is fused by Kalman filter further more.
视觉系统的目标识别与定位是全自主足球机器人系统的基础,它对机器人感知环境起着关键的作用。HIT-III型全自主机器人的视觉系统是由全维视觉系统和前向单目系统组成的双目异构视觉,两个视觉系统采用基于颜色信息的目标识别,可以独立的对目标进行识别和定位,最后利用卡尔曼滤波进行数据融合。
本文把对全自主足球机器人的射门与守门算法的研究转化为对决策系统的研究。在足球机器人系统里,决策系统的任务是将视觉系统传来的场上的数据进行分析,对场上比赛形势做出判断,形成比赛策略,并通过角色的决策模型来规划机器人的运动,完成射门与守门任务。在设计决策系统时,采用了有穷自动机的理论,并构造了各角色的有穷状态机决策模型,每个状态都对应着一个算法,用来控制机器人运动,在状态进行转换时就完成了机器人的运动与相应任务。
最后,经射门与守门实验表明,机器人运动轨迹平滑、实时性高,该决策算法可以应用在全自主足球机器人比赛中;并进一步验证了双目异构视觉系统的可行性和经过卡尔曼滤波算法融合后的定位信息的准确性。
The robot soccer system is a typical competition system of mobile robot, with the character of high request of real time, high dynamic environment, un-predictability, etc., and it associates high technology study with soccer, examining various theories, methods and techniques by the soccer game. This paper is based on autonomous soccer robot system, and the main study is object identification and localization, and shooting arithmetic and goalkeeping arithmetic.
Object identification and localization of vision system is the foundation of autonomous soccer robot system, it plays a pivotal role in apperceiving surroundings for robot. The vision system of HIT-III autonomous soccer robot is binocular heterogeneous vision, composed of omni-vision and monocular vision, each of which can identify objects based on color information and localize objects independently, and the localization data is fused by Kalman filter at last.
In this paper, studying in shooting arithmetic and goalkeeping arithmetic of autonomous soccer robot is converted into designing a decision-making system. In robot soccer system, the function of the decision-making system is that to analyze the sounding data from vision system, to estimate the state of the match, to make a decision, and to control the robot moving to complete the shooting and defense task. A deterministic finite state automaton is used in designing decision-making system, which is constructed for each role. Every state corresponds with arithmetic, which control the robot to move, so when the state is transferring in deterministic finite state automaton, the robot is working to move and complete task.
Finally, experiments showed that, this decision-making arithmetic, with the smooth trajectory of robot motion and high real time, can be used in autonomous soccer robot. And it proves the feasibility of binocular heterogeneous vision and accurately of localization data that is fused by Kalman filter further more.
引文
1 K. Mackworth. On seeing robot[A]. Computer vision: System, theory and applications[M]. Singapore: World Scientific Press, 1993:1~13
2洪炳熔.机器人足球比赛——发展人工智能的里程碑[J].电子世界. 2000, (4):4~5
3 http://baike.baidu.com/
4 T. Ichinose, Y. Takemura, K. Azeura, I. Godler. HIBIKINO-MUSASHI. RoboCup 2006 Bremen. CDROM. Proc. of RoboCup. 2006
5 http://robocup.ksrp.or.jp/hibikino-musashi/paper/
6 A. A. F. Nassiraei, Y. Takemura. Concept of Mechatronics Modular Design for an Autonomous Mobile Soccer robot[C]. CIRA 2007, Jacksonville. 2007:178~183
7 S. Wang, J. M. Siskind. Image segmentation with ratio cut[C]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003. 2003, 25(6):675~690
8 R. C. Gonzalez.数字图像处理[M].阮秋琦,阮宇智等译.第二版.电子工业出版社, 2007:460~498
9 M. Tkalcic, J. F. Tasic. Colour spaces: perceptual, historical and applicational background[C]. The IEEE Region 8 EUROCON 2003. 2003, 1:304~308
10蒋亚军.三种常用颜色模型的比较研究[J].湖南科技学院学报. 2007, 28(4):37~38
11杨静,陈昭炯.不同颜色空间中全局色彩传递算法的分析研究[J].计算机工程与应用. 2007, 43(25):81~82
12杨其宇,彭刚,高健,杨涛,伍翼,王敏,黄心汉.足球机器人系统中几种颜色模型的比较与分析[A].马斯特杯2003年中国机器人大赛及研讨会论文集[C].马斯特杯2003年中国机器人大赛及研讨会,中国北京, 2003.中国北京,中国学术期刊电子杂志社, 2003:318~323
13谭琪.基于全维视觉的目标识别与定位[D].哈尔滨工业大学硕士研究生学位论文. 2007:25~48
14刘伟. RoboCup中型组机器人全景视觉系统设计与实现[D].国防科学技术大学硕士学位论文. 2004:3~81
15 Sooyong Lee, N. M. Amato, J. Fellers. Localization based on visibility sectors using range sensors[C]. IEEE International Conference on Robotics and Automation, 2000. 2000, 4:3505~3511
16杨鹏,高晶,刘作军,万文献.基于全景与前向视觉的足球机器人定位方法研究[J].控制与决策. 2008, 23(1):75~78
17许成珅,蒋平.基于全维视觉的足球比赛机器人目标定位[J].微计算机信息. 2005, 21(8-3):85~87
18卢惠民,刘斐,郑志强.一种新的用于足球机器人的全向视觉系统[J].中国图象图形学报. 2007, 12(7):1243~1248
19阮玉峰.全自主型足球机器人及其智能控制系统设计[D].哈尔滨工业大学硕士研究生学位论文. 2003:33~49
20于芳,李祖枢,王牛.一种全自主足球机器人单目视觉定位的新方法[J].计算机测量与控制. 2007, 15(12):1781~1784
21卢惠民,王祥科,刘斐,季秀才,郑志强,基于全向视觉和前向视觉的足球机器人目标识别[J].中国图象图形学报. 2006, 11(11):1686~1689
22 Jie Tian, Jie Chen, Lihua Dou, Yuhe Zhang. The research of test and evaluation for multisensor data fusion systems[C]. Proceedings of the 4th World Congress on Intelligent Control and Automation, 2002. 2002, 3:2104~2108
23 Qingmei Yang, Jianmin Sun. An Underwater Autonomous Robot Based on Multisensor Data Fusion[C]. The Sixth World Congress on Intelligent Control and Automation, 2006. 2006, 2:9139~9143
24丁锋,姜秋喜,张楠.多传感器数据融合发展评述及展望[J].舰船电子对抗. 2007, 30(3):52~55
25 Enbin Song, Yunmin Zhu, Jie Zhou. The optimality of Kalman filtering fusion with cross-correlated sensor noises[C]. 43rd IEEE Conference on Decision and Control, 2004. 2004, 5:4637~4642
26 B. Sadeghi, B. Moshiri. Second-order EKF and Unscented Kalman Filter Fusion for Tracking Maneuvering Targets[C]. IEEE International Conference on Information Reuse and Integration, 2007. 2007:514~519
27 R. Kalman. A New Approach to Linear Filtering and Prediction Problems[J]. Basic Eng. 1960, (82):34~45
28 Y. Bar-Shalom, X. R. Li. Estimation and Tracking: Principles Techniques and Software[J]. IEEE Antennas and Propagation Magazine. 1993, 38(1):62
29 M. Eggers, T. Khuon. Neural network data fusion concepts and application[C]. Inter-national Joint Conference on Neural Networks, 1990. 1990, 2:7~16
30 J. H. Kotecha, P. M. Djuric. Gaussian particle filtering[C]. IEEE Transac-tions on Signal Processing, 2003. 2003, 51(10):2592~2601
31陈红,蔡晓霞,曾昭勇.一种基于粒子滤波的测向定位跟踪算法[J].武汉大学学报(理学版). 2007, 53(5):609~612
32 R. Siegwart, I. R. Nourbakhsh.自主移动机器人导论[M].李人厚译.西安交通大学出版社, 2006:235~245
33樊恩,聂明新.采用稳态Kalman滤波器简化Kalman滤波器的计算[J].武汉理工大学学报(信息与管理工程版). 2005, 27(5):272~274
34 J. E. Hopcroft, R. Motwani, J. D. Ullman.自动机理论、语言和计算导论[M].刘田,姜晖,王捍贫译.第二版.机械工业出版社, 2004:25~36
35洪炳镕,阮玉峰. HIT-II型全自主足球机器人硬件系统的设计与实现[J].哈尔滨工业大学学报. 2003, 35(9):1025~1028
36柳长安,刘刚,刘春阳.机器人足球防守算法研究[J].哈尔滨工业大学学报. 2004, 36(7):951~953
37刘春阳,柳长安,吴克河.足球机器人的防守策略设计与分析[J].哈尔滨工业大学学报. 2004, 36(7):957~959
38周军,陈盛.基于场地分区的机器人足球守门员防守策略设计[J].河海大学常州分校学报. 2006, 20(3):22~24
39郝宗波,洪炳镕.仿真机器人足球射门动作研究[J].哈尔滨工业大学学报. 2003, 35(9):1102~1104
40 A. Takahashi, Y. Ninomiya. Model-based lane recognition[C]. Proceedings of the 1996 IEEE Intelligent Vehicles Symposium, 1996. 1996:201~206
41 Cheng-Li Jia, Ke-Feng Ji, Yong-Mei Jiang, Gang-Yao Kuang. Road extraction from high-resolution SAR imagery using Hough transform[C]. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005.2005, 1:25~29
42 Yau-Hwang Kuo, Chang-Shing Lee, Chao-Chin Liu. A new fuzzy edge detection method for image enhancement[C]. Proceedings of the Sixth IEEE International Conference on Fuzzy Systems, 1997. 1997, 2:1069~1074
43 N. Kazakova, M. Margala, N. G.Durdle. Sobel edge detection processor for a realtime volume rendering system[C]. Proceedings of the 2004 International Symposium on Circuits and Systems, 2004. 2004, 2:23~26
44 R. K. Satzoda, S. Suchitra, T. Srikanthan. Parallelizing the Hough Transform Computation[J]. IEEE Signal Processing Letters. 2008, 15:297~300
2洪炳熔.机器人足球比赛——发展人工智能的里程碑[J].电子世界. 2000, (4):4~5
3 http://baike.baidu.com/
4 T. Ichinose, Y. Takemura, K. Azeura, I. Godler. HIBIKINO-MUSASHI. RoboCup 2006 Bremen. CDROM. Proc. of RoboCup. 2006
5 http://robocup.ksrp.or.jp/hibikino-musashi/paper/
6 A. A. F. Nassiraei, Y. Takemura. Concept of Mechatronics Modular Design for an Autonomous Mobile Soccer robot[C]. CIRA 2007, Jacksonville. 2007:178~183
7 S. Wang, J. M. Siskind. Image segmentation with ratio cut[C]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003. 2003, 25(6):675~690
8 R. C. Gonzalez.数字图像处理[M].阮秋琦,阮宇智等译.第二版.电子工业出版社, 2007:460~498
9 M. Tkalcic, J. F. Tasic. Colour spaces: perceptual, historical and applicational background[C]. The IEEE Region 8 EUROCON 2003. 2003, 1:304~308
10蒋亚军.三种常用颜色模型的比较研究[J].湖南科技学院学报. 2007, 28(4):37~38
11杨静,陈昭炯.不同颜色空间中全局色彩传递算法的分析研究[J].计算机工程与应用. 2007, 43(25):81~82
12杨其宇,彭刚,高健,杨涛,伍翼,王敏,黄心汉.足球机器人系统中几种颜色模型的比较与分析[A].马斯特杯2003年中国机器人大赛及研讨会论文集[C].马斯特杯2003年中国机器人大赛及研讨会,中国北京, 2003.中国北京,中国学术期刊电子杂志社, 2003:318~323
13谭琪.基于全维视觉的目标识别与定位[D].哈尔滨工业大学硕士研究生学位论文. 2007:25~48
14刘伟. RoboCup中型组机器人全景视觉系统设计与实现[D].国防科学技术大学硕士学位论文. 2004:3~81
15 Sooyong Lee, N. M. Amato, J. Fellers. Localization based on visibility sectors using range sensors[C]. IEEE International Conference on Robotics and Automation, 2000. 2000, 4:3505~3511
16杨鹏,高晶,刘作军,万文献.基于全景与前向视觉的足球机器人定位方法研究[J].控制与决策. 2008, 23(1):75~78
17许成珅,蒋平.基于全维视觉的足球比赛机器人目标定位[J].微计算机信息. 2005, 21(8-3):85~87
18卢惠民,刘斐,郑志强.一种新的用于足球机器人的全向视觉系统[J].中国图象图形学报. 2007, 12(7):1243~1248
19阮玉峰.全自主型足球机器人及其智能控制系统设计[D].哈尔滨工业大学硕士研究生学位论文. 2003:33~49
20于芳,李祖枢,王牛.一种全自主足球机器人单目视觉定位的新方法[J].计算机测量与控制. 2007, 15(12):1781~1784
21卢惠民,王祥科,刘斐,季秀才,郑志强,基于全向视觉和前向视觉的足球机器人目标识别[J].中国图象图形学报. 2006, 11(11):1686~1689
22 Jie Tian, Jie Chen, Lihua Dou, Yuhe Zhang. The research of test and evaluation for multisensor data fusion systems[C]. Proceedings of the 4th World Congress on Intelligent Control and Automation, 2002. 2002, 3:2104~2108
23 Qingmei Yang, Jianmin Sun. An Underwater Autonomous Robot Based on Multisensor Data Fusion[C]. The Sixth World Congress on Intelligent Control and Automation, 2006. 2006, 2:9139~9143
24丁锋,姜秋喜,张楠.多传感器数据融合发展评述及展望[J].舰船电子对抗. 2007, 30(3):52~55
25 Enbin Song, Yunmin Zhu, Jie Zhou. The optimality of Kalman filtering fusion with cross-correlated sensor noises[C]. 43rd IEEE Conference on Decision and Control, 2004. 2004, 5:4637~4642
26 B. Sadeghi, B. Moshiri. Second-order EKF and Unscented Kalman Filter Fusion for Tracking Maneuvering Targets[C]. IEEE International Conference on Information Reuse and Integration, 2007. 2007:514~519
27 R. Kalman. A New Approach to Linear Filtering and Prediction Problems[J]. Basic Eng. 1960, (82):34~45
28 Y. Bar-Shalom, X. R. Li. Estimation and Tracking: Principles Techniques and Software[J]. IEEE Antennas and Propagation Magazine. 1993, 38(1):62
29 M. Eggers, T. Khuon. Neural network data fusion concepts and application[C]. Inter-national Joint Conference on Neural Networks, 1990. 1990, 2:7~16
30 J. H. Kotecha, P. M. Djuric. Gaussian particle filtering[C]. IEEE Transac-tions on Signal Processing, 2003. 2003, 51(10):2592~2601
31陈红,蔡晓霞,曾昭勇.一种基于粒子滤波的测向定位跟踪算法[J].武汉大学学报(理学版). 2007, 53(5):609~612
32 R. Siegwart, I. R. Nourbakhsh.自主移动机器人导论[M].李人厚译.西安交通大学出版社, 2006:235~245
33樊恩,聂明新.采用稳态Kalman滤波器简化Kalman滤波器的计算[J].武汉理工大学学报(信息与管理工程版). 2005, 27(5):272~274
34 J. E. Hopcroft, R. Motwani, J. D. Ullman.自动机理论、语言和计算导论[M].刘田,姜晖,王捍贫译.第二版.机械工业出版社, 2004:25~36
35洪炳镕,阮玉峰. HIT-II型全自主足球机器人硬件系统的设计与实现[J].哈尔滨工业大学学报. 2003, 35(9):1025~1028
36柳长安,刘刚,刘春阳.机器人足球防守算法研究[J].哈尔滨工业大学学报. 2004, 36(7):951~953
37刘春阳,柳长安,吴克河.足球机器人的防守策略设计与分析[J].哈尔滨工业大学学报. 2004, 36(7):957~959
38周军,陈盛.基于场地分区的机器人足球守门员防守策略设计[J].河海大学常州分校学报. 2006, 20(3):22~24
39郝宗波,洪炳镕.仿真机器人足球射门动作研究[J].哈尔滨工业大学学报. 2003, 35(9):1102~1104
40 A. Takahashi, Y. Ninomiya. Model-based lane recognition[C]. Proceedings of the 1996 IEEE Intelligent Vehicles Symposium, 1996. 1996:201~206
41 Cheng-Li Jia, Ke-Feng Ji, Yong-Mei Jiang, Gang-Yao Kuang. Road extraction from high-resolution SAR imagery using Hough transform[C]. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005.2005, 1:25~29
42 Yau-Hwang Kuo, Chang-Shing Lee, Chao-Chin Liu. A new fuzzy edge detection method for image enhancement[C]. Proceedings of the Sixth IEEE International Conference on Fuzzy Systems, 1997. 1997, 2:1069~1074
43 N. Kazakova, M. Margala, N. G.Durdle. Sobel edge detection processor for a realtime volume rendering system[C]. Proceedings of the 2004 International Symposium on Circuits and Systems, 2004. 2004, 2:23~26
44 R. K. Satzoda, S. Suchitra, T. Srikanthan. Parallelizing the Hough Transform Computation[J]. IEEE Signal Processing Letters. 2008, 15:297~300