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rc_decision

This project implements a robotic decision-making system using Behavior Trees (BT) within the ROS ecosystem. It integrates custom nodes for navigation, chassis control, and sensor input handling, enabling autonomous task execution. Key features include interaction with ROS services/actions, real-time behavior tree execution, blackboard-based data sharing, and support for joystick control. Built with BehaviorTree.CPP and leveraging ROS’s navigation stack, it provides modular, testable, and deployable robotic intelligence with logging, visualization, and fault-tolerant capabilities.
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Table of Contents

1. About The Project
   • Built With
2. Getting Started
   • Prerequisites
   • Installation
3. Usage
4. Roadmap
5. Contributing
6. License
7. Contact
8. Acknowledgments

📖 About The Project

This project implements a robotic decision-making system using Behavior Trees (BT) within the ROS ecosystem. It integrates custom nodes for navigation, chassis control, and sensor input handling, enabling autonomous task execution. Key features include interaction with ROS services/actions, real-time behavior tree execution, blackboard-based data sharing, and support for joystick control. Built with BehaviorTree.CPP and leveraging ROS’s navigation stack, it provides modular, testable, and deployable robotic intelligence with logging, visualization, and fault-tolerant capabilities.

Key Features

• Behavior Tree Integration: Modular and extensible task execution framework using BehaviorTree.CPP.
• ROS Navigation Interface: Seamless integration with move_base for goal-based navigation.
• Joystick-Controlled Chassis Movement: Real-time chassis control using joystick input.
• Custom Message/Service/Action Support: Full support for custom-defined .msg, .srv, and .action files.
• Real-Time Execution Logging: Integrated logging system with configurable verbosity levels.
• Visualization Support: Optional integration with Groot for visual debugging of behavior trees.
• Fault Tolerance: Retry, timeout, and preemption mechanisms for robust execution.

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Built With

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📁 Project Structure

Click to expand project structure

rc_decision/
├── .clang-format
├── .clang-tidy
├── .pre-commit-config.yaml
├── CMakeLists.txt
├── package.xml
├── action/
│   └── Fibonacci.action
├── image/
│   ├── 1.png
│   ├── 2.png
│   └── 3.png
├── include/
│   └── rc_decision/
│       ├── bt_action_node.h
│       ├── bt_service_node.h
│       ├── aurora/
│       │   ├── ChassisMove.h
│       │   ├── laser_goal.h
│       │   └── movebase_client.h
│       ├── blackboard/
│       │   ├── RosJoy.h
│       │   └── blackboard.h
│       └── loggers/
│           └── rosout_logger.h
├── launch/
│   ├── RosJoy.launch
│   └── control_loop.launch
├── msg/
│   ├── BehaviorTree.msg
│   ├── NodeParameter.msg
│   ├── NodeStatus.msg
│   ├── StatusChange.msg
│   ├── StatusChangeLog.msg
│   └── TreeNode.msg
├── src/
│   ├── ChassisMove.cpp
│   ├── control_loop.cpp
│   ├── laser_goal.cpp
│   ├── move_base_client.cpp
│   └── loggers/
│       └── rosout_logger.cpp
├── srv/
│   └── AddTwoInts.srv
└── test/
    ├── launch/
    │   ├── test_client.launch
    │   └── test_server.launch
    └── treeNode/
        ├── test_bt.cpp
        └── test_server.cpp

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🚀 Getting Started

This is an example of how you may give instructions on setting up your project locally. To get a local copy up and running follow these simple steps.

Prerequisites

• Ubuntu 18.04 or later
• ROS Melodic or Noetic installed
• catkin workspace configured
• C++14 compiler
• behaviortree_cpp_v3 library installed

Installation

1. Clone the repository into your catkin workspace:

   cd ~/catkin_ws/src
   git clone https://github.com/gdut-robocon/rc_decision.git

2. Build the package:

   cd ~/catkin_ws
   catkin_make

3. Source the workspace:

   source devel/setup.bash

Configuration

• Ensure the ROS navigation stack is running and move_base is active.
• Configure joystick input via RosJoy.launch.
• Modify scaling parameters in ChassisMove.cpp or via ROS parameter server if needed.

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💻 Usage

To start the main behavior tree execution loop:

roslaunch rc_decision control_loop.launch

To test behavior tree functionality with sample tasks:

rosrun rc_decision test_bt

To start the test server (provides Fibonacci action and AddTwoInts service):

rosrun rc_decision test_server

For joystick-controlled chassis movement:

roslaunch rc_decision RosJoy.launch

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🗺️ Roadmap

• Add support for dynamic reconfiguration of behavior trees
• Integrate with SLAM for real-time mapping and navigation
• Implement more advanced error handling and recovery strategies
• Add support for more sensor types (LiDAR, IMU, etc.)
• Enhance visualization with full Groot integration

See the open issues for a full list of proposed features (and known issues).

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🤝 Contributing

Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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Top contributors:

🎗 License

Copyright © 2024-2025 rc_decision.
Released under the MIT license.

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📧 Contact

Email: jialonglongliu@gmail.com

Project Link: https://github.com/gdut-robocon/rc_decision

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