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NDT-MCL #93
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Both https://doi.org/10.1109/ICRA.2013.6630878 and http://dx.doi.org/10.1177/0278364913499415 on how to build NDT based occupancy maps are worth a look too. Implementing the measurement model is straightforward once we have a way to build, update, and query such maps efficiently. Being able to draw an NDT map from a plain occupancy grid (ie. the typical 2D map / floor plan representation) would also be quite useful.
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FYI @Voldivh |
FYI @serraramiro1 |
Should we close this? This has been addressed with #422 . WDYT @hidmic @nahueespinosa |
We have some work ahead still, to polish, benchmark, and demo NDT-MCL in full. This ticket is old though, and I'm having second thoughts about the value of meta-tickets in this project. How about making it a discussion, and keep the useful context? |
Description
This method proposes to relax the hard discretization assumption imposed by grid-based models in common MCL implementations by using a piecewise continuous normal distribution representation (NDT) of the map and measurements to achieve higher accuracy and repeatability. The NDT map is based on a regular grid containing estimated normal distribution parameters of the mapped environment.
Dual-Timescale NDT-MCL extends this idea to localize in highly dynamic environments and solve the SLAM problem.
See:
Definition of done
TBD
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