Welcome to the official GitHub repository for the AI in Robotics course 2024. This course focuses on the integration of Artificial Intelligence techniques, specifically within the domain of robotics.

All the videos, slides, and code for this chapter are organized in our Google Drive folder. You can access them using the link below:

This comprehensive course provides an in-depth exploration of various AI technologies applied in the field of robotics. By combining theoretical knowledge with practical implementations, students will gain a robust understanding of how to enhance robotic systems with AI capabilities. Key topics include:

• Detailed exploration of how computer vision enables robots to perceive and interpret their environment. Topics cover both the underlying principles and the application of CV technologies in real-world robotic scenarios.

• Examination of Convolutional Neural Networks for their pivotal role in recognizing objects and scenes, which are crucial for autonomous robotic functions.

• Introduction to state-of-the-art object detection techniques that allow robots to identify and locate various objects within their environment effectively.

• Study of advanced segmentation methods that enable precise identification and differentiation of objects within an image, crucial for detailed environmental interaction.

• Techniques and algorithms for tracking objects across a sequence of images or video frames, which is vital for interactive and responsive robotic behaviors.

• Comprehensive coverage of Reinforcement Learning, teaching robots to make decisions based on their actions and outcomes to achieve specific goals.

• Integration of RL and CV technologies to develop sophisticated systems that plan and control robotic actions based on complex inputs and learning experiences.

• Utilization of the Webots simulator to provide a realistic environment where students can test and observe the behavior of their robotic models without the need for physical hardware.

This section showcases the avatars of the main collaborators on this project. Click on any avatar to visit their GitHub profile and see their contributions.

hassanyousefzade

mhtayebzadeh

To cite this resource in a publication or academic paper, you can use the following BibTeX entry:

@misc{MJAHMADEE2024,
  author = {Amirkabir University of Technology},
  title = {AI in Robotics Course 2024},
  year = {2024},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/MJAHMADEE/AIinRobotics2024W}}
}

For those who are using the IEEE citation style, the following format can be used:

Amirkabir University of Technology, "Machine Learning Course 2024," GitHub repository, 2024. [Online]. Available: https://github.com/MJAHMADEE/MachineLearning2024W

The course includes detailed reading materials, recorded video lectures, and practical assignments to deepen understanding and provide hands-on experience. Each topic's folder contains dedicated resources for further exploration and study.

We encourage contributions to the course materials and projects. Please fork the repository and submit pull requests with your enhancements or corrections.

For support or inquiries, feel free to open an issue within the repository. We aim to assist and address questions promptly.

This repository's content and code are under the MIT License, allowing for broad usage and distribution with appropriate credit.

Wishing you an exciting and productive journey through the world of AI in Robotics!

🚀 Happy learning!