Subject: Subject Sylbus: Vision-Aided Navigation - 086761

Vision-Aided Navigation - 086761
Credit
Points
3.0
 
Given In
Semester
a
 
  Lecture Exercise Laboratory Project or
Seminar
House
Work
Weekly
Hours
3       5

Determination of the grade according to progress during the semester and a final examination.


Prerequisites: ( Fundamentals in Estimation Theory 086777
and Probability (Ae) 094417 )
or ( Fundamentals in Estimation Theory 086777
and Introduction to Probability H 104034 )


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),

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.T Optimization Using Real Imagery. 4. Develop Algorithms for Belief Space Planning.D Bundle Adjustment Optimization Using Real Imagery. 4. Develop Algorithms for Belief Space Planning.N Using Real Imagery. 4. Dev




System of hours to the semesters
Semester Previous Semester information 01/2016 2016-2017 Winter Semester


Textbooks
PublishedPublisherAuthorsBook
2003cambridge university pressr. hartley and a. zissermanmultiple view geometry in computer vision
2008new york: mcgraw hillj. farrellaided navigation: gps with high rate sensors
2005mit presst. sebastian, w. burgard, and d. foxprobabilistic robotics

Created in 27/05/2017 Time 16:32:09