Multimodal AI in Robotics

• Strong foundation in robotics and AI
• Proficiency in Python and C++
• Knowledge of sensor technologies

Audience

• Robotics engineers
• AI researchers
• Automation specialists

Multimodal AI is key to building advanced robotic systems that can interact with their environment in complex ways.

This instructor-led, live training (online or onsite) is aimed at advanced-level robotics engineers and AI researchers who wish to utilize Multimodal AI for integrating various sensory data to create more autonomous and efficient robots that can see, hear, and touch.

By the end of this training, participants will be able to:

• Implement multimodal sensing in robotic systems.
• Develop AI algorithms for sensor fusion and decision-making.
• Create robots that can perform complex tasks in dynamic environments.
• Address challenges in real-time data processing and actuation.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

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