2020-21 Fall - ELEC3210 - Machine Learning and Information Processing for Robotics

Course

Description

The course is to introduce the basic concepts of information processing techniques used in robotics. Course content include Bayes theory, hidden Markov model, localization and mapping, kernel methods for regression, Gaussian process, classification, support-vector machine (SVM); common sensors, software platform and algorithms used in robotics research.
Course period1/09/2031/12/20
Course levelUG
Course formatLecture