Oct 3rd 2016

Robotics: Estimation and Learning (Coursera)

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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.

Robotics: Estimation and Learning is course 5 of 6 in the Robotics Specialization.

The Robotics Specialization introduces you to how robots sense and reason about the world they live, how they plan three dimensional movements in a dynamic environment and how they fly or run while adapting to uncertainties in the environment. You will be exposed to real world examples with drones, legged robots and driverless cars. The courses build towards a capstone in which you will learn how to program robots to perform a variety of tasks in unstructured, dynamic environments.