Robotics Estimation and Learning
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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Syllabus
Syllabus - What you will learn from this course
Week 1
Gaussian Model Learning
Week 2
Bayesian Estimation - Target Tracking
Week 3
Mapping
Week 4
Bayesian Estimation - Localization
FAQ
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:
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.
Reviews
Good materials for beginners. Assignments are interesting and useful.
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Week 1 and Week 3 are organized much better than Week 2 and Week 4. If you don't have enough time, I recommend that you focus on Week 1 and 3.
Very succinct lectures which provides necessary foundation to learn advanced localization algorithms.
Pretty practical course It' ll involve a good amount of programming. Not quiz and theoretical verification here.
