NOTE:
All dates in the future are subject to change as the semester evolves.
Readings below refer to books listed on the course Resources page
| Date | Topic | Notes |
| Aug. 21 | Course Overview | |
| Aug. 23 | Introduction to Image Processing: grayscale images, filtering, image features, Histogram of Oriented Gradients (HOG) features | Read:
[Corke] 12.2-12.4;
[SNS] 4.3, 4.4
For each of these, the course will focus mainly on the sections cited above, but you can learn lots of useful and interesting things by reading the entire chapters. |
| Aug. 28 | Supervised Learning: inductive learning, cross-validation, k-nearest neighbors | |
| Aug. 30 | Support vector machines, parameter optimization, classification valuation metrics | |
| Sep. 4 | Quiz 1 (in class) After the quiz, collect robots |
Topics for Quiz 1 include material presented in lecture Aug 21-30, and the assigned reading materials. |
| Sep. 6 | Cozmo check. Bring your robots and laptop to class. | |
| Sep. 11 | RANSAC, Robot Programming | Read:
[Corke] 14.2.3 The RANSAC algorithm is introduced here for
the task of estimating the fundamental matrix, but you don't need
to understand the fundamental matrix to understand RANSAC.
[SNS] 4.7.2.4 |
| Sep. 13 | Coordinate Transformations, SO(n), SE(n), composition of transformations | Read:
[Corke] Chapter 2.
You can skip Sections 2.2.1.2-2.2.1.6, and the quaternion stuff in Section 2.2.2,
but be aware that quaternions are pretty cool.
I also quite like the presentation of this material in Chapter 2 of [SHV]. |
| Sep. 18 | Quiz 2
In-class demos |
The quiz will focus on material from the Sep 11 and 13 lectures, but could also include questions dealing with material covered in previous lectures. |
| Sep. 20 | Probability for State Estimation | Read:Chapter 2 of [TBF]. This chapter gives an excellent coverage of probability theory and the development of the Bayes filter. |
| Sep. 25 | Particle Filters | Read:[Corke] Section 6.5 [SNS] Sections 5.1-5.5, and Section 5.6 excluding Section 5.6.8 (which we will cover later) |
| Sep. 27 | Particle Filters (cont) | |
| Oct. 2 | Quiz 3 | |
| Oct. 4 | Guest Lecture Frank Dellaert will talk about very cool stuff. | |
| Oct. 9 | Fall Recess -- No lecture | |
| Oct. 11 | Kalman filtering | Read:
[SNS] Section 5.6.8 [Corke] Appendix H (a somewhat more dense treatment) |
| Oct. 16 | Kalman Filtering (cont) | |
| Oct. 18 | Quiz 4 Graph Search |
The quiz will cover the Kalman filtering lectures.
Read: Various search algorithms are described in [SNS] Section 6.3.1 |
| Oct. 23 | BUG Algorithms | Read: The BUG algorithms are described in [SNS] Section 6.4.1, and in [Choset] Chapter 2. |
| Oct. 25 | Motion Planning in the Plane: Visibility Graphs, Generalized Voronoi Diagrams, Cell Decompositions | Read: These algorithms are described in [SNS] Section 6.3, and in [Choset] Sections 5.1, 5.2 and 6.1. |
| Oct. 30 | Quiz 5
The Configuration Space |
The quiz will cover only graph search.
Read: A light intro to configuration spaces is given in Section 6.3 of [SNS]. A more mathematical treatment is given in [Choset] Chapter 3. |
| Nov. 1 | Sampling-based methods for path planning | Read: [SNS] Section 6.3.1.3 has a terse description of RRTs
[Choset] Sections 7.1 and 7.2 give a more detailed treatment of PRM and RRTs. |
| Nov. 6 | Lab 4 Demo | |
| Nov. 8 | Quiz 6 | This quiz will cover BUG algorithms, the visibility graph, Generalized Voronoi Diagrams, and Cell Decomposition. |
| Nov. 13 | Artificial Potential Fields | Read: [SNS] Section 6.3.2 gives a nice overview of the method.
[Choset] Chapter 4 gives a more detailed treament, including grid-based implementations. |
| Nov. 15 | Lab 5 Demo | |
| Nov. 20 | ||
| Nov. 22 | Thanksgiving | |
| Nov. 27 | Quiz 7 | The quiz will cover configuration space and sampling-based planners |
| Nov. 29 | Quiz 8 | The quiz will cover artificial potential field planning methods |
| Dec. 4 | Lab 6 Demo | |