Introduction
Problem Statement: In many environments, robots face challenges due to their rigid structure, limiting their ability to adapt to different tasks and confined spaces. For example, cleaning robots struggle to efficiently handle both large surfaces and tight corners. Similarly, robots in search-and-rescue missions may need to navigate both open areas and narrow spaces, which requires flexibility and adaptability.
Solution: The origami-based shape-changing robot is designed to tackle these challenges by offering a robot that can dynamically alter its shape. By expanding for large tasks and shrinking for confined spaces, this robot can easily transition between different tasks and environments. Using the **ROS 2 Humble Framework** for smooth trajectory planning and **deep reinforcement learning (TD3)** to optimize navigation, it can efficiently navigate various surfaces while maintaining high adaptability. The robot’s flexible design provides a practical solution for both large-scale operations and precision tasks, offering a perfect balance between versatility and efficiency.
Key Features
- Origami-Based Shape Change: The robot can dynamically alter its shape to adapt to various environments.
- ROS 2 Humble Framework: Used for smooth trajectory planning and surface-specific navigation.
- Real-Time Motion Control: Achieved with the ROS 2 Control Plugin for precise movements.
- TD3 Deep Reinforcement Learning: Enables optimal navigation strategies through machine learning.
Benefits
- Maximized adaptability to various spaces and tasks.
- Seamless autonomous operation with learning capabilities.
- Innovative AI and robotics applications in autonomous navigation and flexibility.
Skills
- ROS 2 Humble Framework
- Python and C++ Programming
- Origami-Based Design Principles
- Deep Reinforcement Learning (TD3)
- Motion Planning and Navigation Algorithms
- Real-Time Control Systems
Media
Credits
A special thank you to all those who contributed to the development of this project:
- Fan Zirui - Designed the innovative origami-based shape-changing robot and provided key insights into its mechanical structure.
- Dr. Zhang Hongying - Provided expert guidance throughout the project, particularly in the areas of robotics design and development.
- National University of Singapore - Provided the platform and resources to conduct this research, facilitating a collaborative effort to push the boundaries of autonomous robotics.
- ROS 2 Community - Thanks to the open-source community for the development of the ROS 2 Humble Framework, which was integral to the robot’s motion planning and navigation.
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