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I am reading particle filtering for robot localisation and specifically the resampling step to avoid particle degeneracy. Can anyone explain me what MC (Monte Carlo) variation means? I saw it couple of times as a benefit of some resampling techniques against others.

For example, "Systematic resampling is the scheme preferred by the authors [since it is simple to implement, takes O(N) time, and minimizes the MC variation]" (Arulampalam et al., 2002).

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  • $\begingroup$ Welcome to Robotics, George. It looks like you copied a line from the paper, "A Tutorial on Particle Filters for Online Nonlinear/Non-Gaussian Bayesian Tracking," by Arulampalam et al. The full quote mentions source [25] - "Systematic resampling [25] is the scheme preferred by the authors", where [25] is, “Monte Carlo filter and smoother for non-Gaussian nonlinear state space models,” by G. Kitagawa. I would, in general, highly suggest following the cited sources if you have questions. $\endgroup$ – Chuck♦ Aug 2 '17 at 19:11
  • $\begingroup$ This is still a good question, though. I'm hoping you get some great answer! :) $\endgroup$ – Chuck♦ Aug 2 '17 at 19:11

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