Introduction to AI in Robotics: Intelligent Machines in Motion
artificial-intelligence-ai.
Course Modules:
Module 1: What is AI in Robotics?
Overview of robotics vs. AI
Key components of an intelligent robotic system
Applications in manufacturing, healthcare, logistics, and defense
Module 2: Perception and Sensors
How robots “see” the world
Cameras, LIDAR, ultrasonic, and infrared sensors
Introduction to computer vision and sensor fusion
Module 3: Reasoning and Decision-Making
Reactive vs. deliberative control
Rule-based logic, machine learning, and probabilistic models
Path planning and obstacle avoidance
Module 4: Motion Planning and Control
Kinematics and dynamics basics
Trajectory generation and execution
Using AI to control robotic arms, wheeled robots, and drones
Module 5: Learning in Robotics
Supervised learning, reinforcement learning in robotics
Imitation learning and self-play
Adaptive robots and online learning systems
Module 6: Capstone Project – Simulate an AI Robot
Choose a robotics simulation (e.g., line follower, warehouse robot)
Build a simple control algorithm using perception and planning
Submit code, simulation screenshots, and a reflection report
Tools & Technologies Used:
Python
ROS (Robot Operating System) – optional
OpenAI Gym, PyBullet, or Webots for simulation
Computer vision: OpenCV
Target Audience:
Beginners in robotics or AI
Students interested in autonomous systems
Engineers exploring intelligent machines
Researchers and hobbyists in robot design
Global Learning Benefits:
Understand how AI powers robotic autonomy
Bridge software and physical systems in real-world tasks
Build foundational knowledge for advanced robotics or drone applications
Start prototyping intelligent robotic behavior in simulation
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