I want to make a list of what knowledge is necessary for sensor fusion. Since it has a wide array of possible applications, it is not clear where to begin studying. Can we please verify add topics that are in-scope, and specify to what extent?:

  1. Digital Signal Processing course
  2. Probability Course
  3. Machine Learning - course at Coursera from Stanford University
  4. Programming robotic car - course at Udacity
  5. Knowledge of Matlab and Simulink - tutorials on mathworks webpage and offline help.
  6. Basic knowledge about integrals, matrices operations, differential equations.
  • 2
    $\begingroup$ Welcome to Robotics.SE! There's a lot of question all rolled up into one. You might consider splitting this into several questions. However, your main question is essentially a list question, which is discouraged on StackExchange in general, as there is no one right answer. Maybe our FAQ can help you rephrase the question in a more answerable way. $\endgroup$
    – ThomasH
    Mar 12, 2013 at 0:05
  • $\begingroup$ Welcome josh131 there's definitely an interesting question (or evenseveral questions) buried in here, so feel free to either edit this question or start a new question (or questions). For an explanation of why we try to avoid list questions, see this answer on teh stack exchange meta site. $\endgroup$
    – Mark Booth
    Mar 12, 2013 at 13:22
  • $\begingroup$ This question is basically no different than This one, except that it is less-well-posed. I think the problem here is the lack of a solid definition about "sensor fusion." I'll edit it then we can revisit closing. For now I think it's valid. $\endgroup$ Mar 13, 2013 at 21:56
  • $\begingroup$ I know it has been a while, but it could be helpful to future viewers if you add the links for "Machine Learning" and below. $\endgroup$
    – koverman47
    Jul 11, 2018 at 15:53

1 Answer 1


You can skip all but 2,6,5, if you want to learn how sensor information is fused to form a consistent estimate of something. 5 is optional but helpful. The best course you can take is a Optimal Estimation / Filtering course, and a Probabilities and Stochastic Processes course. Try MIT Courseware for both of those.

  • $\begingroup$ I have been dabbling with those courses. There are many of them and I'm not sure which would be the best to follow on MIT courseware. I have not found exactly with the name you specified, Optimale Estimation/Filtering. Which one exactly do you recommend? $\endgroup$
    – josh131
    Apr 17, 2013 at 7:20
  • $\begingroup$ This is exactly Optimal Estimation / Filtering. Review the requirements for this course, make sure you satisfy them, then take this course. It's your best bet. $\endgroup$ Apr 17, 2013 at 15:00

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