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Artificial Intelligence for Robotics

Udacity
Training overview
48 hours
Next start date: Free E-Learning: Start Anytime! - Online
E-learning

Course description

Artificial Intelligence for Robots: E-learning from Udacity

Artificial Intelligence for Robots from Udacity

Offered as part of the Georgia Tech Masters in Computer Science, this course is designed to guide learners through all the major systems necessary for running a robotic car. Learners will gain the basics of Artificial Intelligence, including:

  • probabilistic inference
  • localization
  • tracking and control
  • planning and search

A hands-on, project-based learning experience

As part of this of this e-learning course participants will have the opportunity to use what they have learned to solve the problem of a runaway robot that you must chase and hunt down.

Who should attend?

This Artificial Intelligence for Robots course is designed for anyone hoping to learn probabilitic inference, localization, planning and search, tracking and control and other skills necessary for robotics. And have fun doing it!

Pre-Requisites

This program requires some understanding of programming and fluency in mathematics. Experience with Python is helpful but not necessary. The math used will revolve around linear algebra and probability. While course material does not require you to be an expert in either basic familiarity will be very useful.

Find out if this course is right for you - request more information here!

Training Content

Training topics for this Artificial Intelligence for Robots course is dived into 6 Lessons

Localization

  • Localization
  • Total Probability
  • Uniform Distribution
  • Probability After Sense
  • Normalize Distribution
  • Phit and Pmiss
  • Sum of Probabilities
  • Sense Function
  • Exact Motion
  • Move Function
  • Bayes Rule
  • Theorem of Total Probability

Kalman Filters

  • Gaussian Intro
  • Variance Comparison
  • Maximize Gaussian
  • Measurement and Motion
  • Parameter Update
  • New Mean Variance
  • Gaussian Motion
  • Kalman Filter Code
  • Kalman Prediction
  • Kalman Filter Design
  • Kalman Matrices

Particle Filters

  • Slate Space
  • Belief Modality
  • Particle Filters
  • Using Robot Class
  • Robot World
  • Robot Particles

Search

  • Motion Planning
  • Compute Cost
  • Optimal Path
  • First Search Program
  • Expansion Grid
  • Dynamic Programming
  • Computing Value
  • Optimal Policy

PID Control

  • Robot Motion
  • Smoothing Algorithm
  • Path Smoothing
  • Zero Data Weight
  • Pid Control
  • Proportional Control
  • Implement P Controller
  • Oscillations
  • Pd Controller
  • Systematic Bias
  • Pid Implementation
  • Parameter Optimization

SLAM (Simultaneous Localization and Mapping)

  • Localization
  • Planning
  • Segmented Ste
  • Fun with Parameters
  • SLAM
  • Graph SLAM
  • Implementing Constraints
  • Adding Landmarks
  • Matrix Modification
  • Untouched Fields
  • Landmark Position
  • Confident Measurements
  • Implementing SLAM

Course projects

Runaway Robot Final Project

Costs

It is free to start this Artificial Intelligence for Robots course

Estimated time for completion assuming 6 hours per week: Approx. 2 months

2-Week Free Trial: Love it or Leave it

All Udacity courses are offered with a two-week free trial. Learners will have plenty of time to make sure that the program fits their needs. If it's not working out for any reason - user can cancel their subscription fee of charge.

About Udacity

Udacity E-Learning Tech Programs

Udacity E-learning : Online Training from Tech Industry Leaders

Udacity offers a range of courses for the tech industry, designed with both current and aspiring professionals. The tech industry moves fast and keeping up means constantly refreshing your knowledge and sharpening talents.  Data Science Web Development Software Engineering Android...


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