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研究生：	郭秉寰 Kuo, Ping-Huan
論文名稱：	FIRA AndroSot 與 RoboCup 小型人形機器人足球賽模擬器之開發 Development of Simulator for AndroSot in FIRA and Kid-Sized Humanoid Soccer in RoboCup
指導教授：	李祖聖 Li, Tzuu-Hseng S.
學位類別：	碩士 Master
系所名稱：	電機資訊學院 - 電機工程學系 Department of Electrical Engineering
論文出版年：	2010
畢業學年度：	98
語文別：	英文
論文頁數：	145
中文關鍵詞：	模擬器、機器人、足球賽
外文關鍵詞：	FIRA, RoboCup, AndroSot, Simulator, Humanoid Soccer
相關次數：	點閱：93 下載：12
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本論文主要在探討FIRA AndroSot與RoboCup小型人形機器人足球賽模擬器之開發與其策略演算系統。由於人形機器人足球比賽提供了一個動態而且多樣化的環境，因此可以做為多方面研究題材的測試平台。然而針對策略系統而言，如果在沒有硬體架構與視覺系統整合完成情況之下，很難進行測試。為了解決上述問題，本論文提出了一套人形機器人足球比賽的策略模擬系統，以供使用者方便測試策略之可行性與優缺點。在模擬器中，會將使用者編譯完成的動態連結程式庫動態載入至程式中，並可針對使用者策略，選擇AndroSot與RoboCup兩種模擬模式。本論文提出的策略，在AndroSot中主要目標是引導各個機器人執行障礙物規避及合作進攻，以求得勝利。機器人所表現的智慧行為係以電位場導航與模糊控制為基礎的演算法實現。在RoboCup策略中，本論文提出了進攻、防守、與合作的控制策略。而機器人的自主定位是使用蒙地卡羅法，並使用機率分佈的格子地圖來記錄定位的資訊。最後透過模擬與實驗結果，可以充分展現模擬器與控制策略之優越效能與強健性。

This thesis mainly confers the development of simulator for humanoid robot soccer competition and its strategies. The simulator is developed for AndroSot in FIRA and kid-sized humanoid soccer in RoboCup. Due to the robot soccer game presents a dynamic and complex environment, it provides a challenging platform for multi-agent research. Furthermore, if there were some problems occurred in the robot actions and image processing algorithm, it is very difficult to run or test strategy systems. In order to solve these issues, a humanoid robot soccer competition’s strategy simulation system is proposed, which provides developer to test the feasibility and advancement of the game strategy. In this simulator, strategies which compiled to DLL files may be explicitly loaded at run-time. And the simulation mode is selectable (AndroSot or RoboCup) for its strategies. In AndroSot, the soccer robots are manipulated to perform the tasks of obstacle avoidance, collaboration, and competition for victory. In order to achieve the goal, a fuzzy logic based strategy is implemented for AndroSot. To lead the robot toward the target while detouring obstacle simultaneously, a potential field algorithm of obstacle avoidance is proposed. In RoboCup, the control strategy of attacking, defending, and collaborating are also described. The localization method of the strategy is realized via the Monte Carlo Localization (MCL) and the robot’s position is recorded and represented as a position probability grid map. Finally, the simulation and experiment results demonstrate the validity and robustness of the simulator and strategy systems.

Abstract												   		   	 II
Acknowledgment													 III
Contents															 IV
List of Figures								                     VIII
List of Tables													    XIII

Chapter 1. Introduction												1
1 Motivation													1
2 Thesis Organization											3

Chapter 2. Overview of the Robot Soccer System							4
1 Introduction												4
2 Introduction to Robot Soccer Game					    		5
2.1 FIRA Android Soccer Tournament						5
2.2 RoboCup Soccer Humanoid League						7
3 Mechanism Design of the Robot Soccer for AndroSot				8
4 The Hardware of aiRobots-A1									11
4.1 Actuators											12
4.2 Motion Controller				   						14
4.3 Li-Po Batteries										16
5 The Hardware of AndroSot System								17
5.1 Host Computer System									18
5.2 Vision System										18
5.3 Wireless Communication System							19
6 Summary													21

Chapter 3. Simulator for Humanoid Robot Soccer Competition 				22
1 Introduction												22
2 System Architecture						            		23
3 User Guide of the Proposed Simulator							25
3.1 Playing Field					            			25
3.2 The Ball and the Robots			    					27
3.3 The Toolbar					            			31
3.4 The Basic Functions				    				33
3.5 Movement of the Ball				    				36
4 The Tutorial on Creating DLL Files			  					41
5 Extended Mode - Master Level					    			43
6 Summary													45

Chapter 4. Strategy Decision Systems										46
1 Introduction												46
2 The Dynamic Strategy System for AndroSot in FIRA				47
2.1 Overview of Potential Field Navigation Method				47
2.2 Extended Potential Field Navigation Method				51
2.3 Pre-Calculating Information								55
2.4 Design of Fuzzy Controller								62
2.5 The Strategy for Attacker								69
2.6 The Strategy for Defender								70
2.7 The Strategy for Goalkeeper								71
3 The Control Strategy for Kid-Sized Humanoid Soccer in RoboCup	74
3.1 The Control Strategy for Localization						74
3.2 The Control Strategy for Common Behaviors	    		80
3.3 The Strategy for Attacker								82
3.4 The Strategy for Goalkeeper								83
3.5 The Strategy for Reposition								84
4 The Extended Strategy for Actual Competition in AndroSot			85
4.1 The Vision System										86
4.2 The Strategy System									88
4.3 The Motion Control System								89
4.4 Getting Back into Stable Standing							90
5 Summary													91

Chapter 5. Simulation and Experimental Results		 					92
1 Introduction												92
2 Simulation Results of Strategies for AndroSot						93
2.1 Rebound Shooting										93
2.2 Twice Rebound Shooting								94
2.3 The Strategy for Goalkeeper								96
2.4 The Strategy for Defender								98
3 Simulation Results of Strategies for RoboCup						101
3.1 The Strategy for Attacker								101
3.2 The Strategy for Goalkeeper								103
3.3 The Strategy for Reposition								106
4 Experimental Results of Strategies for AndroSot					109
4.1 The Common Behaviors								110
4.2 The Strategy for Attacker								111
4.3 Rebound Shooting										112
4.4 The Strategy for Goalkeeper								113

Chapter 6. Conclusions and Future Works		      					116
1 Conclusions					                			116
2 Future Works			                                    117

References															118
Appendix 															120
Biography															145

                                    

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校內：2015-08-18公開
校外：2015-08-18公開

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