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#	pointmatcher/IO.cpp
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27 changes: 14 additions & 13 deletions README.md
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Expand Up @@ -30,7 +30,7 @@ The library is written in C++ for efficiency with [bindings in Python](doc/index
     
[![Mentioned in Awesome Robotics](https://awesome.re/mentioned-badge.svg)](https://github.com/ahundt/awesome-robotics#point-clouds)
<br>
<sup>
<sup>
&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;
<a href="https://github.com/szenergy/awesome-lidar#basic-matching-algorithms">LIDAR</a>
&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;
Expand All @@ -48,9 +48,9 @@ The library is written in C++ for efficiency with [bindings in Python](doc/index

### Supported OS And Architecture
_libpointmatcher_ is tested on our build system under the following architecture and OS:
- Ubuntu bionic (18.04), focal (20.04) and jammy (22.04)
- Ubuntu bionic (18.04), focal (20.04) and jammy (22.04)
- x86 and arm64/v8

Note:
- _libpointmatcher_ reportedly works on MacOs OsX (latest) and Windows (latest)

Expand All @@ -66,7 +66,7 @@ Execute the following to clone the repository with its submodule:
```shell
git clone --recurse-submodules https://github.com/norlab-ulaval/libpointmatcher.git
```
If _libpointmatcher_ was previously cloned, execute the following to fetch its new submodule
If _libpointmatcher_ was previously cloned, execute the following to fetch its new submodule
```shell
git submodule update --remote --recursive --init
```
Expand All @@ -79,12 +79,12 @@ on your workstation to speed up your local development workflow.

[//]: # (====Body=================================================================================)
# Documentation and Tutorials

**Quick link for the tutorial pages: [Tutorials](http://libpointmatcher.readthedocs.org/).

Those tutorials are written using Markdown syntax and stored in the project's `/doc` folder. Their scope ranges from introductory material on performing point cloud registration to instructions for the more experienced developer on how to extend the library's codebase.
Those tutorials are written using Markdown syntax and stored in the project's `/doc` folder. Their scope ranges from introductory material on performing point cloud registration to instructions for the more experienced developer on how to extend the library's codebase.

Libpointmatcher's source code is fully documented based on doxygen to provide an easy API to developers. An example of this API can be found [here](https://norlab.ulaval.ca/libpointmatcher-doc/), but it is suggested to use the one build for your version in `doc/html`.
Libpointmatcher's source code is fully documented based on doxygen to provide an easy API to developers. An example of this API can be found [here](https://norlab.ulaval.ca/libpointmatcher-doc/), but it is suggested to use the one build for your version in `doc/html`.

libpointmatcher was orginaly developed by [François Pomerleau](mailto:[email protected]) and [Stéphane Magnenat](http://stephane.magnenat.net) as part of our work at [ASL-ETH](http://www.asl.ethz.ch).
It is now maintained by the Northern Robotics Laboratory ([Norlab](https://norlab.ulaval.ca/)), led by François Pomerleau.
Expand All @@ -102,7 +102,7 @@ The library has a light dependency list:
* [Eigen] version 3, a modern C++ matrix and linear-algebra library,
* [boost] version 1.48 and up, portable C++ source libraries,
* [libnabo] version 1.0.7, a fast K Nearest Neighbour library for low-dimensional spaces,

and was compiled on:
* Ubuntu ([see how](/doc/CompilationUbuntu.md))
* Mac OS X ([see how](/doc/CompilationMac.md))
Expand Down Expand Up @@ -131,9 +131,9 @@ bash lpm_install_docker_tools.bash
```


### Compilation & Installation
### Compilation & Installation

For beginner users unfamiliar with compiling and installing a library in Linux, go [here](doc/CompilationUbuntu.md) for detailed instructions on compiling libpointmatcher from the source code.
For beginner users unfamiliar with compiling and installing a library in Linux, go [here](doc/CompilationUbuntu.md) for detailed instructions on compiling libpointmatcher from the source code.

For conveniences, you can use the provided installer script for ubuntu
```shell
Expand Down Expand Up @@ -214,7 +214,7 @@ and/or

If you are interested in learning more about different registration algorithms, we recently put together a literature review surveying multiple solutions. The review is organized in the same way as the library and many examples are provided based on real deployments.

F. Pomerleau, F. Colas and R. Siegwart (2015), "_A Review of Point Cloud Registration Algorithms for Mobile Robotics_", __Foundations and Trends® in Robotics__: Vol. 4: No. 1, pp 1-104. https://doi.org/10.1561/2300000035
F. Pomerleau, F. Colas and R. Siegwart (2015), "_A Review of Point Cloud Registration Algorithms for Mobile Robotics_", __Foundations and Trends® in Robotics__: Vol. 4: No. 1, pp 1-104. https://doi.org/10.1561/2300000035

If you don't have access to the journal, you can download it from [here](https://www.researchgate.net/publication/277558596_A_Review_of_Point_Cloud_Registration_Algorithms_for_Mobile_Robotics).

Expand All @@ -226,7 +226,7 @@ We also produced those freely available data sets to test different registration

![alt tag](http://projects.asl.ethz.ch/datasets/lib/exe/fetch.php?cache=&media=laserregistration:asldataset_weblarge.jpg)

You can download the files in CSV or VTK formats, which are directly supported by the library I/O module.
You can download the files in CSV or VTK formats, which are directly supported by the library I/O module.


# Projects and Partners
Expand All @@ -241,7 +241,8 @@ If you are using libpointmatcher in your project and you would like to have it l
* [Norlab](https://norlab.ulaval.ca/) is maintaining and using the library for its research on autonomous navigation in harsh environments.
* [ANYbotics AG](https://www.anybotics.com) is investigating autonomous navigation algorithms using this library.
* [Point Laz Mining LiDAR Expert](https://www.pointlaz.com/) is scanning mine shafts to ensure infrastructure safety.

* [Point Laz Mining LiDAR Expert](https://www.pointlaz.com/) is scanning mine shafts to ensure infrastructure safety.
* [DREAM lab](https://dream.georgiatech-metz.fr/research/woodseer/) use libpointmatcher to reconstruct wood logs in 3D.
For a larger list of work realized with libpointmatcher, please see the page [Applications And Publications](/doc/ApplicationsAndPub.md).


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12 changes: 6 additions & 6 deletions doc/ImportExport.md
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Expand Up @@ -6,12 +6,12 @@ There exists a myriad of [graphics file formats](http://en.wikipedia.org/wiki/Ca

## Table of Supported File Formats

| File Type | Extension | Versions Supported | Descriptors Supported | Additional Information |
| --------- |:---------:|:------------------:|:---------------------:|---------|
| Comma Separated Values | .csv | NA | yes (see [table of descriptor labels](#descmaptable)) | |
| Visualization Toolkit Files | .vtk | Legacy format versions 3.0 and lower (ASCII only) | yes | Only polydata and unstructured grid VTK Datatypes supported. More information can be found [here](http://www.vtk.org/VTK/img/file-formats.pdf).|
| Polygon File Format | .ply | 1.0 (ASCII only) | yes (see [table of descriptor labels](#descmaptable)) | |
| Point Cloud Library Format | .pcd | 0.7 (ASCII only) | yes (see [table of descriptor labels](#descmaptable)) | |
| File Type | Extension | Versions Supported | Descriptors Supported | Additional Information |
| --------- |:---------:|:-------------------------------------------------:|:---------------------:|---------------------------------------------------------------------------------------------------------------------------------------------------|
| Comma Separated Values | .csv | NA | yes (see [table of descriptor labels](#descmaptable)) | |
| Visualization Toolkit Files | .vtk | Legacy format versions 3.0 and lower (ASCII only) | yes | Only polydata and unstructured grid VTK Datatypes supported. More information can be found [here](http://www.vtk.org/VTK/img/file-formats.pdf). |
| Polygon File Format | .ply | 1.0 (ASCII and binary) | yes (see [table of descriptor labels](#descmaptable)) | Users are encouraged to execute `libpointmatcher` using `double` as the floating precision format to prevent overflows. |
| Point Cloud Library Format | .pcd | 0.7 (ASCII only) | yes (see [table of descriptor labels](#descmaptable)) | |

## Comma Separated Values (CSV) Files

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6 changes: 3 additions & 3 deletions pointmatcher/Documentation.dox
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Expand Up @@ -62,7 +62,7 @@ You can list the available modules with:
pmicp -l
\endcode

If you have compiled libpointmatcher with \ref yaml-cpp enabled, you can configure the ICP chain without any recompilation by passing a configuration file to the \c pmicp command using the \c --config switch. An example file is available in \c examples/data/default.yaml.
Thanks to \ref yaml-cpp , you can configure the ICP chain without any recompilation by passing a configuration file to the \c pmicp command using the \c --config switch. An example file is available in \c examples/data/default.yaml.

\section Understanding Understanding libpointmatcher

Expand All @@ -75,7 +75,7 @@ In libpointmatcher, every module is a class that can describe its own possible p
This text-based configuration aids to explicit parameters used and eases the sharing of working setups with others, which ultimately allows for reproducibility and reusability of the solutions.

The ICP chain takes as input two point clouds, in 2D or 3D, and estimates the translation and the rotation parameters that minimize the alignment error.
We called the first point cloud the \e reference and the second the \e reading.
We called the first point cloud the \e reference and the second the \e reading.
The ICP algorithm tries to align the reading onto the reference.
To do so, it first applies filtering (PointMatcher::DataPointsFilters) to the point clouds, and then it iterates through a sequence of processing blocks.
For each iteration, it associates points in reading to points in reference (PointMatcher::Matcher), rejects outliers (PointMatcher::OutlierFilters) and finds a transformation (PointMatcher::TransformationParameters) of reading that minimizes the alignment error (PointMatcher::ErrorMinimizer).
Expand Down Expand Up @@ -126,7 +126,7 @@ You have to modify 3 files to add a new \ref PointMatcher::DataPointsFilter "Dat
- The types of the parameters are used to properly cast the string value and can be: \c &P::Comp<T>, \c &P::Comp<int>, \c &P::Comp<unsigned>, etc. See \c DataPointsFiltersImpl.h for examples.
- Uncomment and rename the constructor.

- In \c DataPointsFiltersImpl.cpp, copy the implementation of \c IdentityDataPointsFilter at the end of the file including the explicit instantiation (i.e. \c template \c struct \c DataPointsFiltersImpl<float>::YourFilter; and \c template \c struct
- In \c DataPointsFiltersImpl.cpp, copy the implementation of \c IdentityDataPointsFilter at the end of the file including the explicit instantiation (i.e. \c template \c struct \c DataPointsFiltersImpl<float>::YourFilter; and \c template \c struct
\c DataPointsFiltersImpl<double>::YourFilter;).
- Add the constructor if needed.
- At this stage, you should let the implementation of the filter function to hold only the statement that returns the input.
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