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Robotics: Estimation and Learning
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Overview
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.
USD 49
Type: Online
This course includes
- Approx. 15 hours to complete
- Earn a Certificate upon completion
- Start instantly and learn at your own schedule.
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USD 49
Type: Online
This course includes
- Approx. 15 hours to complete
- Earn a Certificate upon completion
- Start instantly and learn at your own schedule.
Taken this course?
Share your experience with other students
Robotics: Estimation and Learning
Created by -
0.00
(0 ratings)
Start Date: February 10th 2021
Course Description
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.
The information used on this page is how each course is described on the Coursera platform.
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About the Instructor
Daniel Lee,University of Pennsylvania
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