This course is part of the Robotics Specialization

4.3
stars
494 ratings

Daniel Lee

30,211 already enrolled

Offered By

Robotics SpecializationUniversity of Pennsylvania

About this Course

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How can robots determine their state and properties of the surrounding environment from noisy sensor measurements in time?  In this module you will learn how to get robots to incorporate uncertainty into estimating and learning from a dynamic and changing world.  Specific topics that will be covered include probabilistic generative models, Bayesian filtering for localization and mapping.

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Course 5 of 6 in the

Robotics Specialization

Approx. 14 hours to complete

English

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Skills you will gain

Particle Filter
Estimation
Mapping

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Course 5 of 6 in the

Robotics Specialization

Approx. 14 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructor

Instructor rating

3.86/5 (17 Ratings)

Daniel Lee

Professor of Electrical and Systems Engineering

School of Engineering and Applied Science

30,211 Learners

1 Course

Offered by

University of Pennsylvania

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Syllabus - What you will learn from this course

Week1

Week 1

4 hours to complete

Gaussian Model Learning

We will learn about the Gaussian distribution for parametric modeling in robotics. The Gaussian distribution is the most widely used continuous distribution and provides a useful way to estimate uncertainty and predict in the world. We will start by discussing the one-dimensional Gaussian distribution, and then move on to the multivariate Gaussian distribution. Finally, we will extend the concept to models that use Mixtures of Gaussians.

4 hours to complete

9 videos (Total 52 min), 3 readings, 1 quiz

9 videos

Course Introduction3mWEEK 1 Introduction1m1.2.1. 1D Gaussian Distribution8m1.2.2. Maximum Likelihood Estimate (MLE)6m1.3.1. Multivariate Gaussian Distribution7m1.3.2. MLE of Multivariate Gaussian4m1.4.1. Gaussian Mixture Model (GMM)4m1.4.2. GMM Parameter Estimation via EM7m1.4.3. Expectation-Maximization (EM)6m

3 readings

MATLAB Tutorial - Getting Started with MATLAB10mSetting Up your MATLAB Environment10mBasic Probability10m

Week2

Week 2

3 hours to complete

Bayesian Estimation - Target Tracking

3 hours to complete

5 videos (Total 21 min)

Week3

Week 3

4 hours to complete

Mapping

4 hours to complete

6 videos (Total 36 min)

Week4

Week 4

3 hours to complete

Bayesian Estimation - Localization

3 hours to complete

6 videos (Total 23 min)

Reviews

4.3

115 reviews

5 stars
58.50%
4 stars
20.85%
3 stars
12.34%
2 stars
4.04%
1 star
4.25%

TOP REVIEWS FROM ROBOTICS: ESTIMATION AND LEARNING

by AVJun 24, 2016

A tough course with few hours of lecture material and some good programming assignments.You will be satisfied by those assignments however .

by NNJun 19, 2016

This is course is really helpful for beginners to understand how probability is useful in Robotics.Assignments are bit tough but worth the time .

by SJAug 6, 2016

Lesson 1 and Lesson 3 are clear. However, homework in Lesson 2 and Lesson 4 is hard to finish because of too few materials in the lesson. Overall, it is a fairly good course.

by DDJan 6, 2019

Excellent exposure to mapping, localization, etc. Would have liked to have odometry included in the week4 assignment.

View all reviews

About the Robotics Specialization

The Introduction to Robotics Specialization introduces you to the concepts of robot flight and movement, how robots perceive their environment, and how they adjust their movements to avoid obstacles, navigate difficult terrains and accomplish complex tasks such as construction and disaster recovery. You will be exposed to real world examples of how robots have been applied in disaster situations, how they have made advances in human health care and what their future capabilities will be. The courses build towards a capstone in which you will learn how to program a robot to perform a variety of movements such as flying and grasping objects.

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
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The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

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Robotics: Estimation and Learning

About this Course

Skills you will gain