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1 | initial version |
Yes you are correct, it is because of the adaptive sample set, see the images from Probabilistic Robotics. The second one is the non adaptive. (M is the number of particles).
2 | No.2 Revision |
Yes you are correct, correct (With the KLD-Sampling-MCL part), it is because of the adaptive sample set, see the images from Probabilistic Robotics. The second one is the non adaptive.
adaptive
(M is the number of particles).
particles).
3 | No.3 Revision |
Yes you are correct (With Ok realized some ambiguity. Dieter refers to non-KLD-Sampling as adaptive based on the KLD-Sampling-MCL part), it is random sampling. (see 8.3).
He also refers to the set of particles as adaptive because of the adaptive sample set, see the images from Probabilistic Robotics. The second one KLD sampling. So I would say it is the non adaptive
Augmented-MCL is the "adaptive" part.
(M is the number of particles).
4 | No.4 Revision |
Ok realized some ambiguity. Dieter refers to non-KLD-Sampling as adaptive based on the random sampling. (see 8.3).
He also refers to the set of particles as adaptive because of the KLD sampling. So I would say it is call the Augmented-MCL "adaptive" MCL already. And that the AMCL package is the "adaptive" part.
AMCL with KLD sampling.
(M is the number of particles).
5 | No.5 Revision |
Ok realized some ambiguity. Dieter refers to non-KLD-Sampling as adaptive based on the random sampling. (see 8.3).
He 8.3), note that this version not adapt the number of particles.
I would call Augmented-MCL "Adaptive" MCL because of adding the random poses. Yes, he also refers to the set of particles as adaptive "adaptive" because of the KLD sampling seen in (8.4) which does not have the random additional sampling. So I would call the Augmented-MCL "adaptive" MCL already. And that Hence the AMCL package is AMCL Adaptive Monte Carlo Localization with KLD sampling.
sampling.
(M is the number of particles).
6 | No.6 Revision |
Ok realized some ambiguity. Dieter refers to non-KLD-Sampling as adaptive based on the random sampling. (see 8.3), note that this version not adapt the number of particles.
I would call Augmented-MCL "Adaptive" MCL because of adding the random poses. Yes, he also refers to the set of particles as "adaptive" because of the KLD sampling seen in (8.4) which does not have the random additional sampling. addition of poses. Hence the AMCL package is Adaptive Monte Carlo Localization with KLD sampling.
(M is the number of particles).