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

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