Perception in Robotics course, at Skoltech, MS in Data Science, during T3, 2024. About us: we are the Mobile robotics Lab.
This repository includes all material used during the course: Class notes and problem sets.
- Instructor: Gonzalo Ferrer
- Teaching Assistant: Kazii Botashev
- Teaching Assistant: Ivan Gerasimov
For the logistics, this course will be taught offline (in class) including a lecture and sometimes a small seminar following.
For each lecture, all material will be included in the folder seminar/L*
, and you will find the class notes, the handwritten notes as a result of the class and a short exercise we will do in class. We recommend you to print the class notes and we strongly recommend to write your own notes on the printed document while following the class.
- L01: The Expectation Operator
- L02: Gaussian PDFs
- L03: Motion and Sensor Models
- L04: Gaussian Marginalization and Conditioning
- L05: Bayes Filter and Kalman Filter
- L06: EKF and Localization
- L07: Particle Filter and Monte-Carlo Localization
- L08: EKF SLAM with known correspondences
- L09: GraphSLAM
- L10: Data Association
- L11: Pose SLAM
- L12: 3D Poses and Rigid Body Transformations
- L13: Point Cloud Alignment
- L14: Mapping
- L15: Introduction to Visual SLAM
Deadline dates for submitting problem sets, in the folder PS*
:
- 8-Feb-2024, PS1: Gaussians and Visualization
- 20-Feb-2024, PS2: Localization
- 7-March-2024, PS3: SLAM
Final project. Teams of 3 students solving an open project. The final project could be either of the following, where in each case the topic should be closely related to the course:
- An algorithmic or theoretical contribution that extends the current state-of-the-art.
- An implementation of a state-of-the-art algorithm. Ideally, the project covers interesting new ground and might be the basis for a future conference paper submission or product.
You are encouraged to come up with your own project ideas, yet make sure to pass them by Prof. Ferrer before you submit your abstract
Logistics:
Logistics:
- Ideally 3-5 students per project (the scope of multi-body projects must be commensurate).
- Proposal: 1 page description of project + goals for milestone. This document describes the initial proposal and viability of the project.
- Presentations: The presentation will be 10 minutes long; There will be some minutes for questions after the presentation.
- Paper: This should be a IEEE conference style paper, i.e., focus on the problem setting, why it matters and what is interesting/novel about it, your approach, your results, analysis of results, limitations, future directions. Cite and briefly survey prior work as appropriate but do not re-write prior work when not directly relevant to understand your approach.
- Evaluation: Each team will evaluate their colleagues’ presentations. Instructions will be provided the presentation day.
For reference, we have previous lecture repositories (class23) but there are modifications with respect to the current year.