Basic Information
Inertial and Dead Reckoning Navigation, Probabilistic Information Fusion, Vision Aided Navigation, Simultaneous Localization And Mapping, Imu Pre-integration, Visual-inertial Bundle Adjustment, Cooperative Navigation and Slam (centralized and Distributed), Active State Estimation and Belief-space Planning. Learning Outcomes# After Completion of The Course The Student Will Know How To# 1. Develop and Implement Vision-aided Navigation and Slam Algorithms. 2. Derive and Implement Probabilistic Formulations For Cooperative Information Fusion, Van and Slam. 3. Implement and Solve Standard Bundle Adjustment Optimization Using Real Imagery. 4. Develop Algorithms For Belief Space Planning.
Faculty: Aerospace Engineering
|Undergraduate Studies
|Graduate Studies
Pre-required courses
44202 - Random Signals or 86733 - Random Processes in Aerospace Systems or 234247 - Algorithms 1
Semestrial Information
Weekly Hours
3 Academic Credit • 3 Lecture Hours
Responsible(s)
Vadim Indelman
Notes
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הקורס ילמד באנגלית. שימוש בפיאציה במקום מודל
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Weekly Hours
3 Academic Credit • 3 Lecture Hours
Responsible(s)
Vadim Indelman
Notes
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הקורס ילמד באנגלית.
Exams
Session A: 07-02-2023Quizzes
Session A: 28-12-2022-
הבחינה תתקיים בחדר לימוד הקורס: 283
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Weekly Hours
3 Academic Credit • 3 Lecture Hours
Responsible(s)
Vadim Indelman
Notes
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הקורס ילמד בשפה האנגלית.
Exams
Session A: 03-02-2022 09:00 - 12:00- ה.אויר 240. 241.
Quizzes
Session A: 28-12-2021 14:30 - 16:30- ה.אויר 150, 240,
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