===== B3M33MKR: Mobile and and Collective Robotics  (winter term 2018/19)  =====

==== Seminars organization ====
  * Students are expected to work in teams by two (exceptions allowed after consultation with teacher).
  * Each group is expected to work with a real robot.
  * Majority of the work is planned as an **individual work** of the group (you can work anytime the room is available).
  * Students are expected to **ask** - ask early, ask often.  
  * Teachers will be personally available during the regularly scheduled hours, otherwise over the e-mail (but don't expect answers in order of minutes)
  * **Charge the robot** every time you stop working with it.
  * Keep **all** source codes on CSV (SVN or GIT). The **disk** on the on-board computer can be **erased anytime** (No complains - you were warned).
  * You are sharing the robots with others, **keep it clean** (physically as well as the disk space). Don't mess with others' stuff.
  * Create your own ROS workspace. Use a naming convention mkr_<group_name>_ws.


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===Introduction===
  *  {{:courses:b3m33mkr:turtlebot.pdf|slides}}   


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===Assignments===

  * Each team is asked to implement selected algorithms presented on lectures:
    * Multi-robot motion coordination 
      *  {{:courses:b3m33mkr:mkr2018_mrc-slides.pdf|slides}}           
      *  {{:courses:b3m33mkr:mkr2018_mrc.tar.gz|Code}} 
    * Kalman filter and Extended Kalman filter for localization
      *  {{:courses:b3m33mkr:labs-slides-kalman-en.pdf|Slides}} 
      *  {{:courses:b3m33mkr:kalman.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:particle_filter_ros.tar.gz|Particle filter code for ROS}}
      *  {{:courses:b3m33mkr:pf-slides.pdf|Slides}}
      *  {{:courses:b3m33mkr:videos.zip|Video with motion model demonstration}}

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===Getting the seminar credit===

To get the seminar credit, student must:

    * Participate and actively work at all seminars (up to 2 absences without excuse will be tolerated),
    * Create a working algorithms solving *all* the tasks,
    * Present a well-written and documented source code,
    * Understand the presented solution and source code (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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