A baby version of my bearing vision only EKF slam on our robot

It's the first version my EKF slam on this robot. The goal is fusion odometry with monocular vision. No ground truth, but from the video we can see the odometry can not close the loop and the slip make the trajectory can not be a circle. But the result from EKF_slam works here, it correct the angle of rotation when the robot have a sharp turn.

Structure from motion

1, After you get essential matrix , you can use SVD to recover rotation and translation matrix. But the translation vector is normalized vector or say unit vector or say up to a scale. The rotation matrix is correct.
2, You can never get this scale factor from images without additional information. If you are using stereo vision, you know the baseline, so you can recover the scale factor by this baseline, then you can get Euclidean coordinate. OTHERWISE you can use some known landmark whose world coordinate is already known.
3, So, what's the structure or motion? Now you should get Euclidean transformation is not only transformation. It's a children of metric transformation which is children of affine transformation. All above transformation are children of projective transformation. From multi-view image, you just can recover to metric transformation with some constraint about the camera model.
4, The different between metric and euclidean is a scale factor. That means metric transformation can change object's size or line's length and rotation , translation. But euclidean is just contain rotation and translation.



It's really difficulty to understand these geometry stuff. But if I feel difficult, so do other guys. Who win depend on who can continue and insist on.

Open Source SLAM Software

Author Description Link
Kai Arras
The CAS Robot Navigation Toolbox, a Matlab simulation toolbox for robot localization and mapping.
www.cas.kth.se/toolbox/index.html

Tim Bailey Matlab simulators for EKF-SLAM, UKF-SLAM,and FastSLAM 1.0 and 2.0.
www.acfr.usyd.edu.au/homepages/academic/tbailey/software/index.html

Mark Paskin Java library with several SLAM variants, including Kalman filter, information filter, and thin junction tree forms. Includes a Matlab interface.
www.stanford.edu/~paskin/slam/

Andrew Davison Scene, a C++ library for map-building and localisation. Facilitates real-time single camera SLAM.
www.doc.ic.ac.uk/~ajd/Scene/index.html

Jos ́ Neira
e Matlab EKF-SLAM simulator that demonstrates joint compatibility branch-and-bound data association.
http://webdiis.unizar.es/~neira/software/slam/slamsim.htm


Dirk H ̈hnel
a C language grid-based version of FastSLAM.
www.informatik.uni-freiburg.de/~haehnel/old/download.html

Various Matlab code from the 2002 SLAM summer school.
www.cas.kth.se/slam/toc.html

Table 2: Online Datasets
Author Description Link
Jose Guivant, Juan Nieto Numerous large-scale outdoor datasets, notably and Eduardo Nebot the popular Victoria Park data.
www.acfr.usyd.edu.au/homepages/academic/enebot/dataset.htm


Chieh-Chih Wang Three large-scale outdoor datasets collected by the Navlab11 testbed.
www.cs.cmu.edu/~bobwang/datasets.html


Radish (The Robotics Many and varied indoor datasets, including large-Data Set Repository) area data from the CSU Stanislaus library, the
Intel Research Lab in Seattle, the Edmonton Con-
vention Centre, and more.
http://radish.sourceforge.net/

IJRR (The International IJRR maintains a webpage for each article, often Journal of Robotics Research containing data and video of results. A good example is a paper by Bosse et al. [3], which has data from Killian Court at MIT.
www.ijrr.org/contents/2312/abstract/1113.html