===== AE3M33MKR: Mobile and and Collective Robotics  (winter term 2017/18)  =====
==== Seminars organization ====
  * Students are expected to work in teams by two.
  * Each team is asked to implement selected algorithms presented on lectures:
    * Iterative Closest Point for continuous localization. Volunteers can implement also variants of ICP: Iterative Matching Range Point (IMRP) and Iterative Dual Correspondence (IDC)
      * {{:courses:ae3m33mkr:2017-mkr_icp.tar.gz|Code}}
      * {{:courses:ae3m33mkr:output.avi|Video example}}    
      * {{:courses:ae3m33mkr:lu-milios-laser.pdf|Paper about ICP, IMRP, and IDC}}
    * Kalman filter and Extended Kalman filter for localization
      *  {{:courses:a3m33mkr:mkr2016_kf-slides.pdf|Slides}} 
      *  {{:courses:a3m33mkr:mkr2014_kf.tar.gz|Code}} 
    * Particle filter for global localization
      *  {{:courses:b3m33mkr:motion-model.tar.gz|Motion model code}}
      *  {{:courses:b3m33mkr:particle_filter.tar.gz|Particle filter code}}
      *  {{:courses:b3m33mkr:pf-slides.pdf|Slides}}
  * Seminar credit allowance conditions:
    * Participation and active work at all seminars (up to 2 absences without an excuse will be tolerated).
    * Presentation of working algorithms solving *all* the tasks and
    * Understanding of the code presented by each team member.


/*
        {{:courses:a3m33mkr:mkr2014_icp.tar.gz|Code}} z
      *  {{:courses:ae3m33mkr:output.avi|video example}}    
    * Kalman filter and Extended Kalman filter for localization
      *  {{:courses:a3m33mkr:mkr2014_kf-slides.pdf|Slides}} 
      *  {{:courses:a3m33mkr:mkr2014_kf.tar.gz|Code}} 
    * Partical filter for global localization
      *  {{mkr2015_pf.tar.gz|Code}} 
 * A SVN repository will be created for each group. It is expected that students will use it regularly. 
*/


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