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mp2p_icp

C++ libraries for multi primitive-to-primitive (MP2P) ICP algorithms and flexible point cloud processing pipelines. mp2p_icp is used in the mola_lidar_odometry framework:

• Main library documentation and C++ API
• License: New BSD 3-Clause (Note that each module of MOLA has its own license)

Introduction

The project provides these C++ libraries:

• mp2p_icp_map: Provides the mp2p_icp::metric_map_t generic metric map container and related utilities for working with point cloud data structures. Metric map files with extension *.mm are serializations of instances of this class.
• mp2p_icp: With ICP algorithms, matchers (point-to-point, point-to-plane, point-to-line, covariance-to-covariance, adaptive), solvers (Horn, OLAE, Gauss-Newton), and quality evaluators. It depends on mp2p_icp_map.
• mp2p_icp_filters: With point cloud filtering and manipulation algorithms including decimation, voxelization, statistical outlier removal, edge/plane extraction, and various geometric transformations. It depends on mp2p_icp_map.

Command-Line Applications

The full repository also includes these applications (see apps/ directory):

Data Conversion Tools

• kitti2mm: Converts KITTI dataset LIDAR binary files (.bin) with (X,Y,Z, Intensity) data into mp2p_icp metric map files (.mm). Supports custom layer names, numeric IDs, and label strings.

• txt2mm: Converts plain-text point cloud data (TXT/CSV) into metric map (.mm) files. Supports multiple formats: XYZ, XYZI, XYZIRT, XYZRGB, with configurable column mapping and layer names.

• sm2mm: Converts a simple map (.simplemap) from a SLAM mapping session into a metric map (.mm) using a configurable processing pipeline. Essential for post-processing SLAM outputs into structured metric representations.

Data Export Tools

• mm2ply: Exports metric map layers to PLY point cloud files. Supports both ASCII and binary formats, selective field export, and preserves all point attributes (coordinates, colors, intensities, etc.).

• mm2txt: Exports metric map layers as space-delimited CSV/TXT files with header rows. Ideal for data analysis in spreadsheet applications or custom processing pipelines. Supports selective layer and field export.

• mm2las: Exports metric maps to industry-standard LAS 1.4 format with Point Format 8 support. Includes automatic color mapping, extra dimensions for custom fields. Compatible with CloudCompare, QGIS, and ArcGIS.

Map Processing & Analysis Tools

• mm-filter: Applies mp2p_icp_filters pipelines to metric map files. Can operate in pipeline mode (applying complete YAML-defined filter chains) or rename mode (simply renaming layers). Supports custom plugin loading.

• mm-info: Displays a summary of metric map contents including layers, point counts, and metadata.

• mm-georef: Extracts or injects geo-referencing information between metric map files (.mm) and standalone georeferencing files (.georef).

Visualization Tools

• mm-viewer: GUI application to visualize metric map (.mm) files. Supports loading additional 3D scenes and trajectory files in TUM format.

• icp-log-viewer: Interactive GUI for debugging ICP pipelines. Visualizes ICP log files (.icplog) with autoplay mode and detailed inspection of registration results. Essential for understanding and optimizing ICP algorithm performance.

ICP Execution Tools

• icp-run: Standalone program to execute ICP pipelines from the command line.

SimpleMaps Manipulation

• sm-cli: Swiss-army knife for simple map (.simplemap) manipulation. Commands include: info (analyze contents), cut (extract by keyframe index), trim (extract by bounding box), join (merge maps), level (make horizontal), tf (apply SE(3) transform), export-keyframes (save trajectories as TUM), and export-rawlog (convert to RawLog format).

Key Features and Components

Key C++ classes provided by this project (see full documentation):

Core Data Structures

• mp2p_icp::metric_map_t: A generic data type to store raw or processed point clouds, including support for multiple layers, segmented data, and discrete extracted features.

ICP Algorithms and Matchers

• mp2p_icp::ICP: A uniform API for matching generic point clouds with support for:
  • Point-to-Point matching (various distance metrics)
  • Point-to-Plane matching (planes extracted from point clouds)
  • Point-to-Line matching (edges/lines extracted from point clouds)
  • Covariance-to-Covariance matching (Gaussian distributions)
  • Adaptive matching (automatically selects best matcher)

Solvers

• Horn’s method: Closed-form solution for point-to-point alignment
• OLAE (Optimal Linear Attitude Estimator): For attitude/rotation estimation
• Gauss-Newton: Iterative solver for complex matching scenarios

Filters and Generators

The mp2p_icp_filters library provides extensive filtering capabilities:

• Decimation: FilterDecimate, FilterDecimateVoxels, FilterDecimateAdaptive
• Outlier removal: FilterSOR (Statistical Outlier Removal), FilterVoxelSOR

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Changelog for package mp2p_icp

2.4.1 (2026-01-27)

• Add more unit tests
• Update README to keep it in sync with the provided apps and libraries
• Merge pull request #29 from MOLAorg/fix/cov Fix bugs in covariance estimation for some cases
• fix covariance estimation bugs; add unit tests for cov2cov
• Update commit for mola_common
• Merge pull request #28 from MOLAorg/feat/mm-viewer-3d-layers mm-viewer: add CLI flags to load overlaid 3D scenes for visualization
• mm-viewer: add CLI flags to load overlaid 3D scenes for visualization
• Contributors: Jose Luis Blanco-Claraco

2.4.0 (2026-01-21)

• Merge pull request #27 from MOLAorg/feat/new-filter-voxel-sor
• Add new unit test for class factory
• Add new FilterVoxelSOR filter
• Merge pull request #26 from MOLAorg/feat/mm2las
• Add mm2las CLI tool
• Contributors: Jose Luis Blanco-Claraco

2.3.1 (2026-01-14)

• Merge pull request #25 from MOLAorg/feat/naive-decimate Add trivial FilterDecimate for fast downsampling without spatial awareness
• lint fixes
• Add trivial FilterDecimate for fast downsampling without spatial awareness
• Parameterizable: add virtual base dtor
• Remove the NormalizeIntensity stage in the demo pipelines; visualization does that already
• docs: fill missing manpages
• docs: add sm2mm pipelines page
• Clarify map layers and simple maps descriptions Updated references to CMetricMap and CGenericPointsMap in the documentation for clarity and accuracy.
• Contributors: Jose Luis Blanco-Claraco

2.3.0 (2026-01-08)

• Merge pull request #24 from MOLAorg/feat/mm2txt-select-fields mm2txt and mm2ply now have a --export-fields flag
• mm2txt and mm2ply now have a --export-fields flag
• Merge pull request #23 from MOLAorg/fix/some-deprecations Fix usage of deprecated cloud types
• Provide shortcut names for common cloud field names
• More deprecated cloud usage
• FIX bug: FilterDecimateVoxel, if using flatten, did not propagate all input cloud fields
• Fix usage of some deprecated cloud types
• FilterSOR: create output layers even if input is empty
• FilterDeskew: propagate input fields even if the cloud is empty
• FilterByExpression: show debug-level stats
• FilterNormalizeIntensity: do not throw on empty clouds
• Merge pull request #22 from MOLAorg/feat/new-filters Add new filter FilterRenameLayer
• Added filter FilterRenameLayer
• mm2txt: prepare for deprecated classes in 3.0.0
• FilterAdjustTimestamps: new method 'None' to bypass filter
• Fix: sm2mm did not attach to ParameterSource the final_filter elements
• sm2mm: did not observe the optional profiler parameter for the final_filter stage
• Fix: FilterMLS did not properly copy all point fields when using upsampling
• Fix: FilterAbsoluteTimestamp now also works for accumulated points in one layer
• Contributors: Jose Luis Blanco-Claraco

2.2.1 (2026-01-06)

• Merge pull request #21 from MOLAorg/feat/abs-stamp-filter Added new filter: FilterAbsoluteTimestamp
• Fix the logic of the FilterEdgePlane filter parameters
• Added new filter: FilterAbsoluteTimestamp
• mm2txt: also export uint8 fields (missing in last release)
• Merge pull request #20 from MOLAorg/feat/more-unit-tests More unit tests
• Add generators unit tests

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