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The problem you are asking about is one of the difficult issues in robotics: Localization. One of its sub-problems is to take noisy sensor data, and find the best match to a pre-existing map. This has been studied for decades, with no "best" algorithm discovered for either the flat 2D case, or the 3D case you seem to be asking about. This brief answer should give you enough keywords to search on.
If you have a way to visualize & rescale the 3D data, often a human can do this once by trial and error far faster than an algorithm can.
| | 2 | No.2 Revision |
The problem you are asking about is one of the difficult issues in robotics: Localization. One of its sub-problems is to take noisy sensor data, and find the best match to a pre-existing map. This has been studied for decades, with no "best" reasonably-quick algorithm discovered for either the flat 2D case, or the 3D case you seem to be asking about. This brief answer should give you enough keywords to search on.
If you have a way to visualize & rescale the 3D data, and you only need to do it a few times, often a human can do this once by trial and error far faster than an algorithm can.
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