課程大綱： Artificial Intelligence (AI) for Robotics培訓
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
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