UMich 500-Level Mobile Robotics Course

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Deep Learning UMich-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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Comments
  • Questions about Adjoint Matrix on SE(2) and SE(3)

    Questions about Adjoint Matrix on SE(2) and SE(3)

    Hi! First of all, thank you for providing these invaluable materials. :)

    I've studied these materials to fully understand invariant EKF, but there's a question about the Adjoint matrix in matrix_groups/odometry_propagation_se2.m and matrix_groups/odometry_propagation_se3.m.

    In matrix_groups/odometry_propagation_se2.m, adjoint matrix is defined as:

    % SE(2) Adjoint
robot.Ad = @(X) [X(1:2,1:2), [X(2,3); -X(1,3)]; 0 0 1];

    and in matrix_groups/odometry_propagation_se3.m, the adjoint matrix is defined as:

    % SE(3) Adjoint
robot.Ad = @(X) [X(1:3,1:3), skew(X(1:3,4))*X(1:3,1:3); zeros(3), X(1:3,1:3)];

    The point is that the forms of adjoints are different from the one explained in Lecture 08, i.e. [R 0; P^R R]. (1:44:30 @ https://www.youtube.com/watch?v=k2miimTn6rk)

    Could you explain why these adjoints have a different forms? Thank you in advance!

    opened by LimHyungTae 3
  • Correction to Matrix_Lie_Groups_note

    Correction to Matrix_Lie_Groups_note

    Hi,

    First of all, thanks for sharing those well-prepared materials as open-source, I highly benefitted from them.

    I just wanted to offer a correction to slides/07_Matrix_Lie_Groups_note.pdf. In the first page, wedge notation should be written as wx = [0, -w(3), w(2); w(3), 0, -w(1); -w(2), w(1), 0] In the file (and also in the video), it's written as -wx. Also, the matrices of the basis (G1, G2, G3) need to be written accordingly. In the current form [G1, G2]=-G3 instead of G3.

    Thank you, Best regards

    opened by gokhanalcan 1
Owner
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