The AI robotics industry is rapidly growing, driving demand for professionals who can implement intelligent robotic systems in real-world settings. In this AI for Robotics course, you'll explore how AI enables robots to perform complex tasks across diverse applications - from logistics and manufacturing to healthcare and autonomous navigation. We'll dive into advanced AI techniques for perception, manipulation, reasoning, and learning, and examine how these capabilities are integrated into robotic systems. You'll gain hands-on experience training deep learning models for tasks such as object detection, classification, and segmentation. The course also covers the AI software development life cycle, including data preparation, model training, and validation, with a focus on the unique challenges of deploying AI in robotics.

Learning Outcomes
Through discussion, technical demonstration and hands-on practice, you will learn to

• Design, develop, and deploy AI-driven applications for real-world robotic systems.
• Translate real-world use cases into effective AI-powered robotics solutions across various industries such as logistics, manufacturing, and healthcare.  
• Apply machine learning techniques such as computer vision, sensor fusion, and decision-making models to enable robotic perception, control and autonomy.

Topics Include

• Industry use cases and case studies in AI for robotics
• Robotics architecture
• Data acquisition and sensor fusion
• SLAM (simultaneous localization and mapping)
• Computer vision
• Object detection and segmentation
• Autonomous mobile robots
• Natural language processing
• Foundation models for robotics
• Vision-language-action models
• Demonstrations and project presentations
• Deep learning applications

Skills Needed

Students should be proficient in programming languages, such as C++ or Python. Knowledge of AI/ML solutions and related frameworks is suggested as well as familiarity with algebra and higher-level mathematics.