- 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
AI agents are being integrated with robotics for real-world decision-making, autonomous navigation, and industrial automation.
This instructor-led, live training (online or onsite) is aimed at advanced-level robotics engineers, AI researchers, and automation specialists who wish to develop AI-driven autonomous robotic systems for complex tasks and human-AI collaboration.
By the end of this training, participants will be able to:
- Understand the role of AI agents in robotic decision-making and automation.
- Implement AI-driven navigation and obstacle avoidance.
- Develop human-AI collaborative robotic systems.
- Deploy AI-powered perception and control systems in robots.
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 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
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