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Course Outline
Introduction to AI Agents in Robotics
- Overview of AI applications in robotics
- Types of AI agents in robotic systems
- Challenges in integrating AI with robotics
Machine Learning and AI for Robotics
- Reinforcement learning for robotic control
- Supervised and unsupervised learning for robot decision-making
- Transfer learning and domain adaptation in robotics
AI-Driven Perception and Sensing
- Computer vision for robotic perception
- Sensor fusion and data processing
- AI-enhanced object detection and recognition
Autonomous Navigation and Path Planning
- AI-based obstacle avoidance
- Path planning with deep learning
- Simulating autonomous navigation in Gazebo
Human-AI Collaboration in Robotics
- Understanding human-robot interaction
- Developing assistive and cooperative robotic systems
- Ethical and safety considerations
Industrial and Service Robotics with AI
- AI applications in manufacturing and logistics
- AI-driven robotic process automation (RPA)
- Future trends in AI and robotics integration
Deploying AI-Powered Robotics Systems
- Optimizing AI models for real-world robotics
- Deploying AI-driven robotic solutions in production
- Evaluating system performance and adaptability
Summary and Next Steps
Requirements
- Strong understanding of AI and machine learning principles
- Experience with robotics frameworks such as ROS
- Proficiency in Python or C++ for AI-driven robotics
Audience
- Robotics engineers
- AI researchers
- Automation specialists
21 Hours
Testimonials (1)
Trainer responding to questions on the fly.
