Artificial Intelligence (AI) for Robotics Training Course

Introduction

Overview of Artificial Intelligence (AI) and Robotics

• Computer-simulated versus physical
• Robotics as a branch of AI
• Applications for AI in robotics

Understanding Localization

• Locating your robot
• Using sensors to assess location and environment
• Probability exercises

Learning About Robot Motion

• Exact and inexact motions
• Sense and move functions

Using Probability Tools

• Bayes’ rule
• Theorem of total probability

Estimating Vehicle State Using Kalman Filter

• Gaussian processes
• Measurement and motion
• Kalman filtering (code, prediction, design, and matrices)

Tracking Your Robotic Car Using Particle Filter

• State space dimension and brief modality
• Robot class, robot world, and robot particles

Exploring Planning and Search Methods

• A* search algorithm
• Motion planning
• Compute cost and optimal path

Programming Your AI Robot

• First search program and expansion grid table
• Dynamic programming
• Computing value and optimal policy

Using PID Control

• Robot motion and path smoothing
• Implementing PID controller
• Parameter optimization

Mapping and Tracking Using SLAM

• Constraints
• Landmarks
• Implementing SLAM

Troubleshooting

Summary and Conclusion