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Course Outline
Introduction to Multimodal AI in Robotics
- The role of multimodal AI in robotics
- Overview of sensory systems in robots
Multimodal Sensing Technologies
- Types of sensors and their applications in robotics
- Integrating and synchronizing different sensory inputs
Building Multimodal Robotic Systems
- Design principles for multimodal robots
- Frameworks and tools for robotic system development
AI Algorithms for Sensor Fusion
- Techniques for combining sensory data
- Machine learning models for decision-making in robotics
Developing Autonomous Robotic Behaviors
- Creating robots that can navigate and interact with their environment
- Case studies of autonomous robots in various industries
Real-Time Data Processing
- Handling high-volume sensory data in real time
- Optimizing performance for responsiveness and accuracy
Actuation and Control in Multimodal Robots
- Translating sensory input into robotic movement
- Control systems for complex robotic tasks
Ethical Considerations in Robotic Systems
- Discussing the ethical use of robots
- Privacy and security in robotic data collection
Project and Assessment
- Designing, prototyping and troubleshooting a simple multimodal robotic system
- Evaluation and feedback
Summary and Next Steps
Requirements
- Strong foundation in robotics and AI
- Proficiency in Python and C++
- Knowledge of sensor technologies
Audience
- Robotics engineers
- AI researchers
- Automation specialists
21 Hours
Testimonials (1)
I feel I get the core skills I need to understand how the ROS fits together, and how to structure projects in it.
