Robot Soccer Simulation Course
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⚽Robot Soccer Simulation Course
Robot Soccer Simulation Course
Welcome to the 3v3 Simulated Soccer Match! You don't need any experience with machinery, nor do you need a physical robot. As long as you can write strategy logic, your team of robots will play exactly as you command and envision. This competition is based on the robot models and simulation environment of the Booster Robotics Platform, and follows the match rules of the RoboCup.
This page provides a guide to our competition-oriented tutorials, which will guide you all the way from "Starting a Match in Five Minutes" to optimizing your strategies and winning. The tutorials feature indepth content including explanations, code snippets and exercises.
Let's get started! 🚀
Who are the tutorials suitable for？
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Anyone with basic Python proficiency: Get comfortable with the Vibe Coding workflow while learning the necessary background in robotics and simulation.
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Developers who want to compete：Build from the fundamentals to practical strategies such as positioning and zoning. Progress from simply being able to compete to developing a winning strategy.
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Instructors and Student teams：Each chapter contains exercises and extended reading materials, which can be used as training materials for the 3v3 simulation competition.
Quick Start
2.
Obtain the strategy code（choose either method）：
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Method 1: Create it within Booster Studio
Open Booster Studio > New Agent > Select 3v3 Simulated Soccer Agent scenario, and the system will automatically generate the strategy code.
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Method 2 : Download or clone the open source repository
3.
Run a match：
Open the aforementioned code project in Studio, and once the environment is ready, select Virtual Robot, click the hammer and the run button on the top , and you will see the robot team play football according to the default strategy.
4.
Start learning：
As you work through the course, try modifying the code and observing the results. Continue refining and optimizing the strategy as you go.
Document Directory
Module number | Module | Topic | Study time |
1 | Learn about Simulated Soccer Matches | Understand the match rules and agent roles; get your game strategy up and running | 15 minutes |
2 | Overview of Strategy Code | Understand the three-layer architecture clearly, and what happens during a single frame of the 30 Hz main loop. | 80 minutes |
3 | In-depth Understanding of the Finite-state Machine | Use Phase to label the current game situation, then dispatch to the appropriate act* function. | 80 minutes |
4 | Use Context to judge match dynamics | Understand the world snapshot for each frame: ball, teammates, opponents, and referee data. | 60 minutes |
5 | Understanding the Player class | Mastering a Robot's Remote Control: Positioning, Kicking, and High-Level Actions | 60 minutes |
6 | Use store to design cross-frame strategies | Giving Strategy a Memory: State Retention, Hysteresis, Cooldown, and Edge Detection | 60 minutes |
7 | Parameter Tuning | Centralized parameter management | 30 minutes |
8 | Thematic Optimization: Set Piece Offense | Fill in the missing parts of our set plays, writing offensive scripts according to the type of set piece | 80 minutes |
9 | Special Topic Optimization: Set Piece Defense | Fill in the missing parts of opponent set plays, implementing wall formation, double-teaming, and zone defense | 60 minutes |
10 | Topic Optimization : Partitioning Strategy | Switch the entire team's formation and role assignments based on the ball's zone/region | 60 minutes |
11 | Topic Optimization: Movement and Obstacle Avoidance Strategy | Enable robots to avoid obstacles and move more intelligently | 80 minutes |
Appendix A | Appendix: FAQs and Optimization Directions | Common pitfalls and actionable improvement checklist | 20 minutes |
Appendix B | Supplementary - Extended Readings and Resources | Official documentation, open-source repositories, and extended learning resources | 20 minutes |
New participants are encouraged to work through the articles in order. Start with article 1 to get familiar with the controls and experience a match, then work through articles 2-7 to build further understanding step by step: Architecture (know where the code is) → finite-state machine (know what to do and when) → Perception (know what you can observe) → Control (know what you can command) → Memory (know how to coordinate across frames) → Parameter Tuning (know how to optimize the existing strategy to the best). After mastering the main content, you can move on to the special topics, which explain the optimization ideas that set apart the top rankings. You don't need to read the last two appendixes thoroughly; refer to them when you get stuck in debugging Common Issues, and refer to Extended Reading for further learning.