Difference between revisions of "Robotics Teaching Assistant lectures (Como)"
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==5th lecture== | ==5th lecture== | ||
| + | * Kalman Filter | ||
| + | * Kalman Filter example: falling body | ||
| + | * Extended Kalman filter | ||
| + | * Extended Kalman filter localization | ||
| + | * Correspondances, data association and Mahalanobis distance | ||
| + | * Qualitative introduction to Monte Carlo Localization and Particle filters | ||
Slides with animations [[File:Robotics-ceriani-ese-05-anim.pdf]] | Slides with animations [[File:Robotics-ceriani-ese-05-anim.pdf]] | ||
Handout [[File:Robotics-ceriani-ese-05-handout.pdf]] | Handout [[File:Robotics-ceriani-ese-05-handout.pdf]] | ||
Revision as of 09:02, 8 June 2012
Materials used in the Tutorial part of Robotics course (academic year 2011-2012, Como)
1st lecture
- Homogeneous coordinates for points in 2D and 3D
- Rotation and translation in 2D and 3D homogeneous coordinate
- Transformation inversion and composition.
- Lines in 2D homogeneous coordinates, duality with points, line intersection and line joining two points
- The line at the infinity (2D)
- Brief introduction to conics
- 2D projective transformation introduction
Slides with animations File:Robotics-ceriani-ese-01-anim.pdf
Handout File:Robotics-ceriani-ese-01-handout.pdf
2nd lecture
- Projective 2D transformations (Homographies) of points, lines and conics
- Homography estimation and image rectification
- Hierarchy of transformations (isometries, similarities, affine, homographies)
- Vanishing points
- Parametric lines and Cross Ratio (with exercize)
- Affine reconstruction
- 3D projective geometry: points and planes, quadrics, transformations, vanishing points and lines
- Brief recall to art and usage of vanishing points
- Some videos and images examples
- Image definition, Camera system, Thin lenses approximation, Fresnel law, depth of field
- Pin hole model, Intrinsic camera matrix
- Extra exercises with cross ratio
Slides with animations File:Robotics-ceriani-ese-02-anim.pdf Videos:
To see videos in the presentation you have to download and extract them into a folder named "videos" in the same folder of the slide file Video are visible in the pdf file in Windows using Acrobat Reader, in Linux using Okular
Handout File:Robotics-ceriani-ese-02-handout.pdf
3th lecture
- Pin hole model recall
- Projection Matrix
- Interpretation line
- Image of origin and vanishing points
- Angle of view
- Radial and tangential distortion model
- Camera calibration (Matlab Camera Calibration Toolbox [1])
- Epipolar geometry
- Fundamental matrix
- Features in image
- Thresholding, Filtering, Smoothing, Gradient
- Canny edge detector
- Hough transformation for lines extraction
- Corners
- Template matching: patches and SIFT
- Final Exercize on Camera Geometry
Slides with animations File:Robotics-ceriani-ese-03-anim.pdf
Handout File:Robotics-ceriani-ese-03-handout.pdf
4th lecture
- Mobile robot localization
- Taxonomy of localization problems
- Probability recall
- Bayes formula and bayes filter
- Markov Localization
Slides with animations File:Robotics-ceriani-ese-04-anim.pdf
Handout File:Robotics-ceriani-ese-04-handout.pdf
5th lecture
- Kalman Filter
- Kalman Filter example: falling body
- Extended Kalman filter
- Extended Kalman filter localization
- Correspondances, data association and Mahalanobis distance
- Qualitative introduction to Monte Carlo Localization and Particle filters
Slides with animations File:Robotics-ceriani-ese-05-anim.pdf
