Automotive Environment Sensing
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Automotive environment sensors |
Credits: 5 |
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Contact hours: 28 lectures /28 lab |
Assessment type: exam |
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Course coordinator: Tamás Bécsi, PhD, associate professor
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Instructors: |
Course Plan 2019
Week |
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Lecture |
Lab (Matlab exercises) |
2019.02.06 |
1 |
Introduction (PDF) |
A humble engineers guide to computational complexity (and also the answer to when the World will end) (ZIP) |
2019.02.13 |
2 |
Introduction to probabilistics (PDF) |
Simple Robot with Bayes Rule discrete localization (TXT) |
2019.02.20 |
3 |
Localization and Bayes Filtering (PDF, Livescript results) |
Particle Filter Localization, Bayes-KF estimation (ZIP) |
2019.02.27 |
4 |
State Estimation,Kalman Filters, EKF (PDF) |
Various KF/EKF object tracking/state estimation examples (ZIP) |
2019.03.06 |
5 |
SLAM (PDF) |
EKF SLAM problem (ZIP) |
2019.03.13 |
6 |
Environment representation and Occupancy Grid Mapping (PDF) |
Occupancy Grid maps (ZIP) |
2019.03.20 |
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Spring Break |
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7 |
Exam week |
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2019.04.03 |
8 |
Sensing and Measurement (PDF) |
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2019.04.10 |
9 |
Faculty profession day |
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2019.04.17 |
10 |
Radar (PDF) |
Radar demonstration measurement |
2019.04.24 |
11 |
Lidar demonstration measurement |
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2019.05.01 |
12 |
International Labor Day |
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2019.05.08 |
13 |
Exam week |
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2019.05.15 |
14 |
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