- This course explores the integration of AI into robotics, focusing on how AI-powered robots can enhance productivity, safety, and automation in various industries. It is designed for robotics engineers and enthusiasts who wish to incorporate AI into their robotic designs and systems.
- Level: Intermediate
- Prerequisites: Basic knowledge of robotics and programming.
- Assessments: Weekly micro-assessments, final project.
Week 1 - Introduction to AI in Robotics
Learning OutcomeUnderstand the fundamentals of AI integration in robotics.
1.1 The role of AI in robotics: Automation, perception, and decision-making.
1.2 Key components of AI-powered robotics: Sensors, actuators, and AI models.
1.3 Different types of robots enhanced by AI (autonomous robots, collaborative robots).
Practical Component
Build a simple AI-powered robotic system using available AI tools.
Week 2 - Perception and Environment Sensing with AI
Learning OutcomeLearn how AI can enable robots to perceive and interact with their environment
2.1 Using AI for computer vision in robotics (object detection, recognition, and tracking).
2.2 AI in sensor fusion: Combining multiple sensors for better environmental understanding.
2.3 AI for spatial awareness and navigation (SLAM - Simultaneous Localization and Mapping).
Practical Component
Integrate computer vision and sensors to enable a robot to navigate an environment.
Week 3 - Robot Control and Decision Making with AI
Learning OutcomeUnderstand AI algorithms that drive decision-making in robots.
3.1 Reinforcement learning for robot control and decision-making.
3.2 AI-based motion planning and path optimization.
3.3 AI in human-robot interaction: Voice, gestures, and touch.
Practical Component
Program a robot to make autonomous decisions using reinforcement learning.
Week 4 - AI for Industrial Robotics and Automation
Learning OutcomeDiscover how AI optimizes industrial robots in manufacturing and assembly lines.
4.1 AI in collaborative robots (cobots) for industrial environments.
4.2 Using AI to improve precision, speed, and safety in industrial robotics.
4.3 Predictive maintenance and AI-based diagnostics for robotics systems.
Practical Component
Create an AI-based solution for robotic optimization in an industrial setup.
Week 5 - AI for Healthcare Robotics
Learning OutcomeLearn how AI-powered robots are transforming the healthcare industry.
5.1 AI for surgical robots: Enhancing precision and outcomes.
5.2 Robotic assistants in patient care and rehabilitation.
5.3 AI-powered medical imaging robots and diagnostic assistants.
Practical Component
Design an AI-powered robot solution for healthcare applications.
Week 6 - Capstone Project: Building an AI-Powered Robot
Learning OutcomeApply AI techniques to create a fully functional robot.
6.1 Develop an AI-based robot with perception, decision-making, and autonomous behavior.
6.2 Peer review and feedback.
6.3 Final project presentation and evaluation.
Practical Component
Present a fully functional AI-powered robot showcasing autonomous capabilities.