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  • Microforce measurement

    COVID INSTRUCTIONS


    This lab will be conducted in person. During the lab, a maximum of 4 students plus the instructor will be present in the lab. For this reason, it will be crucial that precautions against the spread of corona virus are taken. 

    If you experience any symptoms or have been in close contact with a person who has tested positive in the 10 days before the day you have to attend the lab you are expected not to visit campus and contact the lab instructor as soon as possible (shahriar.haeri@aalto.fi). The lab instructor depending on the situation will help you on how to proceed. 


    PREHEARING and LAB SESSION INSTRUCTIONS

    1. Book a time slot for prehearing session for your group. 
    2. Go through the lab book and answer the questions in the lab book under "Prehearing assignment" section
    3. Go through the MATLAB templates code and complete the code as explained in the lab book and comments in the code  
    4. Upload the answers to questions (typed in MS words or Latex) and the completed MATLAB code under the "Prehearing assignment return box" no later than 27 April
    5. Take part in the remote prehearing session. The instructor will ask questions individually to make sure group members have an acceptable understanding about the topic, and we will check the  MATLAB code together
    6.  Book a time slot for a lab session for your group
    7.  Prepare and fix your codes if needed as instructed in the prehearing session! You will use your own MATLAB code to operate the system during the lab session
    8. Upload your MATLAB code under "lab session return box" at least 24 hours prior to your lab session  
    9. All the group members should take part in the lab session at once (if one or several members of the group are unable to take part in the session due to COVID related issues, contact the lab instructor through email and keep your teammates as CC 
    10. Submit your lab report in two weeks from the time you took part in the lab session     

     

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Sensor fusion with Kalman filter