UMich 500-Level Mobile Robotics Course

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Deep LearningUMich-ROB-530-public
Overview

MOBILE ROBOTICS: METHODS & ALGORITHMS - WINTER 2022

University of Michigan - NA 568/EECS 568/ROB 530

For slides, lecture notes, and example codes, see https://github.com/UMich-CURLY-teaching/UMich-ROB-530-public

Playlist of the lectures on YouTube: https://www.youtube.com/watch?v=pH4Pkmey2_E&list=PLdMorpQLjeXmbFaVku4JdjmQByHHqTd1F

Course description: Theory and application of probabilistic and geometric techniques for autonomous mobile robotics. This course presents and critically examines contemporary algorithms for robot perception. Topics include Bayesian filtering; stochastic representations of the environment; motion and sensor models for mobile robots; algorithms for mapping, localization; application to autonomous marine, ground, and air vehicles.

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UMich CURLY teaching resources
GitHub Repository
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