commit 979d9521a5e184f8ef57b5becb4e8acc19e28a82
Author: MagDish <2717360869@qq.com>
Date:   Mon May 6 19:31:36 2024 +0800

    first commit

diff --git a/README.md b/README.md
new file mode 100644
index 0000000..adc0f2a
--- /dev/null
+++ b/README.md
@@ -0,0 +1,51 @@
+# FC Portugal Codebase <br> for RoboCup 3D Soccer Simulation League
+
+![](https://s5.gifyu.com/images/Siov6.gif)
+
+## About
+
+The FC Portugal Codebase was mainly written in Python, with some C++ modules. It was created to simplify and speed up the development of a team for participating in the RoboCup 3D Soccer Simulation League. We hope this release helps existing teams transition to Python more easily, and provides new teams with a robust and modern foundation upon which they can build new features.
+
+
+## Documentation
+
+The documentation is available [here](https://docs.google.com/document/d/1aJhwK2iJtU-ri_2JOB8iYvxzbPskJ8kbk_4rb3IK3yc/edit)
+
+## Features
+
+- The team is ready to play!
+    - Sample Agent - the active agent attempts to score with a kick, while the others maintain a basic formation
+        - Launch team with: **start.sh**
+    - Sample Agent supports [Fat Proxy](https://github.com/magmaOffenburg/magmaFatProxy) 
+        - Launch team with: **start_fat_proxy.sh**
+    - Sample Agent Penalty - a striker performs a basic kick and a goalkeeper dives to defend
+        - Launch team with: **start_penalty.sh**
+- Skills
+    - Get Ups (latest version)
+    - Walk (latest version)
+    - Dribble v1 (version used in RoboCup 2022)
+    - Step (skill-set-primitive used by Walk and Dribble)
+    - Basic kick
+    - Basic goalkeeper dive
+- Features
+    - Accurate localization based on probabilistic 6D pose estimation [algorithm](https://doi.org/10.1007/s10846-021-01385-3) and IMU
+    - Automatic head orientation
+    - Automatic communication with teammates to share location of all visible players and ball
+    - Basics: common math ops, server communication, RoboViz drawings (with arrows and preset colors)
+    - Behavior manager that internally resets skills when necessary
+    - Bundle script to generate a binary and the corresponding start/kill scripts
+    - C++ modules are automatically built into shared libraries when changes are detected
+    - Central arguments specification for all scripts
+    - Custom A* pathfinding implementation in C++, optimized for the soccer environment
+    - Easy integration of neural-network-based behaviors
+    - Integration with Open AI Gym to train models with reinforcement learning
+        - User interface to train, retrain, test & export trained models
+        - Common features from Stable Baselines were automated, added evaluation graphs in the terminal
+        - Interactive FPS control during model testing, along with logging of statistics
+    - Interactive demonstrations, tests and utilities showcasing key features of the team/agents
+    - Inverse Kinematics
+    - Multiple agents can be launched on a single thread, or one agent per thread
+    - Predictor for rolling ball position and velocity
+    - Relative/absolute position & orientation of every body part & joint through forward kinematics and vision
+    - Sample train environments
+    - User-friendly interface to check active arguments and launch utilities & gyms