Work Sessions Schedule¶
| Lecture Date | Place | Topics | Suggested Reading |
08.01@12:15-14:00 |
PR101 | Course overview, Background overview | Ross-Wright |
13.01@14:15-16:00 |
L5 | 1. Physical sensors, Preimages | Fraden Ch. 1, 2 |
15.01@14:15-16:00 |
L5 | 2. Preimages, Transfer functions, Calibration | Fraden Ch. 1, 2, and SF Ch. 1,2 |
| HW0, QUIZ1 | |||
20.01@14:15-16:00 |
L5 | 3. Virtual Sensors | SF Ch. 3.1 and 3.2 |
22.01@14:15-16:00 |
L5 | 4. Larger state spaces, Environmental entities | SF Ch. 3.1 and 3.2 |
| HW1, QUIZ2 | |||
27.01@14:15-16:00 |
L5 | 5. More sensor types, Sensor dominance, Spatial sensor fusion | SF Ch. 3.3 and 4.1, Gezici |
29.01@14:15-16:00 |
L5 | 6. Spatial sensor fusion, Time parameters | SF Ch. 3.3 and 4.1 |
| HW2, QUIZ3 | |||
03.02@14:15-16:00 |
L5 | 7. Sensors with memory, Sensors that misbehave | SF Ch. 3.4 |
05.02@14:15-16:00 |
L5 | 8. Temporal filtering, examples | SF Ch. 4.2.1-3 |
| HW3, QUIZ4 | |||
10.02@14:15-16:00 |
L5 | 9. Temporal filtering (cont'd), Nondeterministic and probabilistic (Bayesian) filters | SF Ch. 4.2.4-4.2.6 |
12.02@14:15-16:00 |
L5 | 10. Nondeterministic and probabilistic (Bayesian) filters (cont'd), Kalman Filter | SF Ch. 4.2.4-4.2.6 |
| HW4, QUIZ5 | |||
17.02@14:15-16:00 |
L5 | 11. Kalman Filter | |
19.02@14:15-16:00 |
L5 | 12. Particle Filters, SLAM, Visual Odometry | SF Ch. 4.4, Särkkä, Scaramuzza |
| HW5 | |||
24.02@14:00-17:00 |
L5 | Final Exam |
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