        Artificial Intelligence (AI) for Robotics培训

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