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add code, how to, and acknowledgment
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‎.gitignore‎

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*.swo
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*.swp

‎CMakeLists.txt‎

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cmake_minimum_required(VERSION 2.8.3)
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project(rms)
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set(CMAKE_CXX_STANDARD 17)
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set(CMAKE_CXX_STANDARD_REQUIRED ON)
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set(CMAKE_CXX_EXTENSIONS OFF)
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find_package(catkin REQUIRED COMPONENTS
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roscpp
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nodelet
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sensor_msgs
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pcl_ros
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mrs_lib
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)
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# TSL Robin Map for voxelization
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add_subdirectory(thirdparty/robin-map)
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# Point Cloud Library
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find_package(PCL REQUIRED)
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# Eigen
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find_package(Eigen3 REQUIRED)
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set(Eigen_INCLUDE_DIRS ${EIGEN3_INCLUDE_DIRS})
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set(Eigen_LIBRARIES ${Eigen_LIBRARIES})
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set(LIBRARIES
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RMS RMSNodelet
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)
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catkin_package(
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INCLUDE_DIRS include
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LIBRARIES ${LIBRARIES}
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CATKIN_DEPENDS roscpp nodelet sensor_msgs pcl_ros mrs_lib
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DEPENDS Eigen
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)
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include_directories(
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include
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${catkin_INCLUDE_DIRS}
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${PCL_INCLUDE_DIRS}
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${Eigen_INCLUDE_DIRS}
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)
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link_directories(${PCL_LIBRARY_DIRS})
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add_definitions(${PCL_DEFINITIONS})
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add_library(RMS
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src/histogram.cpp
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src/rms.cpp
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)
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add_dependencies(RMS
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${${PROJECT_NAME}_EXPORTED_TARGETS}
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${catkin_EXPORTED_TARGETS}
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)
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target_link_libraries(RMS
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${catkin_LIBRARIES}
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${PCL_LIBRARIES}
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${Eigen_INCLUDE_DIRS}
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tsl::robin_map
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)
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add_library(RMSNodelet
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src/histogram.cpp
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src/rms.cpp
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src/rms_nodelet.cpp
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)
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add_dependencies(RMSNodelet
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${${PROJECT_NAME}_EXPORTED_TARGETS}
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${catkin_EXPORTED_TARGETS}
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)
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target_link_libraries(RMSNodelet
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${catkin_LIBRARIES}
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${PCL_LIBRARIES}
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${Eigen_INCLUDE_DIRS}
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tsl::robin_map
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)
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## --------------------------------------------------------------
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## | Install |
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## --------------------------------------------------------------
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install(TARGETS ${LIBRARIES}
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ARCHIVE DESTINATION ${CATKIN_PACKAGE_LIB_DESTINATION}
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LIBRARY DESTINATION ${CATKIN_PACKAGE_LIB_DESTINATION}
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RUNTIME DESTINATION ${CATKIN_GLOBAL_BIN_DESTINATION}
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)
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install(DIRECTORY launch config
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DESTINATION ${CATKIN_PACKAGE_SHARE_DESTINATION}
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)
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install(DIRECTORY ./
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DESTINATION ${CATKIN_PACKAGE_SHARE_DESTINATION}
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FILES_MATCHING PATTERN "*.xml"
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)

‎README.md‎

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22

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[![RMS](./fig/snapshot.jpg)](https://www.youtube.com/watch?v=Y9ZlRrX1UBY)
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* novel method for sampling large 3D LiDAR point clouds
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* replacement for voxelization
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* pipelines using **RMS** are faster (lower latency) and more accurate (less drift)
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* quick sampling of 3D LiDAR point clouds
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* pipelines using **RMS** are fast (low latency) and accurate
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* designed for **real-time LiDAR-based** 6-DoF odometry/SLAM pipelines
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* both point-based (ICP-like) and feature-based (LOAM-like) methods
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* potentially improving most L, LI, LVI, LV pipelines
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* **single parameter only -> depends on the SLAM pipeline (and not the environment!)**
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* **single parameter only: [lambda](https://github.com/ctu-mrs/RMS/blob/master/config/default.yaml)**
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* depends on the SLAM pipeline (and not the environment!)
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* tuned just once given your pipeline
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* deterministic (no data for learning needed)
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* when is it (probably) not going to perform well:
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* when is it not going to perform well (most probably):
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* the data have large orientation changes between two consecutive frames (tens of degrees)
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* under heavy noise (such as dust clouds)
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* under heavy noise
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#### Code & How to
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The code will be made available upon acceptance.
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## Paper
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Published in IEEE RA-L --- [pdf](https://arxiv.org/pdf/2312.07337.pdf).
2019

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#### Paper
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Submitted to IEEE RA-L on December 1, 2023.
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Preprint available at [arXiv](https://arxiv.org/pdf/2312.07337.pdf).
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## Code & How to
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#### How to cite
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### Installation
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1) Install prerequisities (`mrs_lib`, `PCL`):
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```bash
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curl https://ctu-mrs.github.io/ppa-stable/add_ppa.sh | bash
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apt-get install ros-noetic-mrs-lib ros-noetic-pcl-ros
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```
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@article{petracek2023rms,
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title = {{RMS: Redundancy-Minimizing Point Cloud Sampling for Real-Time Pose Estimation in Degenerated Environments}},
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author = {Petracek, Pavel and Alexis, Kostas and Saska, Martin},
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year = {2023},
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journal = {arXiv:2312.07337},
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note = {Submitted to IEEE RA-L on December 1, 2023}
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2) Clone and build via `catkin`
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```bash
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cd <ROS1_WORKSPACE>/src
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git clone [email protected]:ctu-mrs/RMS.git
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catkin build
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```
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### How to use
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1) Launch as nodelet:
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```bash
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roslaunch rms rms_nodelet.launch NS:=<NAMESPACE> points_in:=<POINTS IN TOPIC> points_out:=<POINTS OUT TOPIC>
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```
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2) Use as library in your code:
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- add `rms` among dependencies in `CMakeLists.txt` and `package.xml` and include the `<rms/rms.h>` header file
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- basic usage: `<rms/rms.h>` and use as in [src/rms_nodelet.cpp](https://github.com/ctu-mrs/RMS/blob/master/src/rms_nodelet.cpp) example
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```cpp
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#include <rms/rms.h>
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...
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// Initialize
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ros::NodeHandle nh;
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mrs_lib::ParamLoader param_loader(nh, "RMS");
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RMS rms = RMS(param_loader);
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...
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// Use
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sensor_msgs::PointCloud2::Ptr msg = ...;
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rms->sample(msg); // 'msg' now contains sampled data
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```
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- **example**: `RMSNodelet` implemented in [src/rms_nodelet.cpp](https://github.com/ctu-mrs/RMS/blob/master/src/rms_nodelet.cpp)
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### Example
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[WORK IN PROGRESS] To be added in coming days.
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## How to cite
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```tex
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@article{petracek2024rms,
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author = {Petracek, Pavel and Alexis, Kostas and Saska, Martin},
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title = {{RMS: Redundancy-Minimizing Point Cloud Sampling for Real-Time Pose Estimation}},
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journal = {IEEE Robotics and Automation Letters},
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year = {2024},
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volume = {9},
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number = {6},
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pages = {5230--5237},
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doi = {10.1109/LRA.2024.3389820}
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}
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```
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#### Acknowledgment
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To be added upon acceptance.
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## Acknowledgment
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This work was supported
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- by CTU grant no. SGS23/177/OHK3/3T/13,
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- by the Czech Science Foundation under research project No. 23-06162M,
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- by the European Union under the project Robotics and advanced industrial production (reg. no. CZ.02.01.01/00/22_008/0004590), and
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- by the Research Council of Norway Award NO-321435.

‎config/default.yaml‎

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lambda: 0.004 # <0, 1> | Alg 1: L5 | tune for your estimation pipeline
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K: 10 # number of bins | Alg 1: L4 | should not need to be changed
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voxelization:
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input: 0.2 # (0, inf) (m) | applied before RMS | Alg 1: L3 | lower: higher timing, higher: lower timing
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output: 0.2 # <0, inf) (m) | applied after RMS

‎include/rms/histogram.h‎

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#pragma once
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#include <vector>
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#include <iostream>
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#include <cmath>
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#include <algorithm>
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#include <set>
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namespace rms
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{
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// key: point index, value: GFH norm
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using t_gfh = std::pair<size_t, float>;
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using t_indices = std::vector<size_t>;
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/* //{ class Histogram1D */
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class Histogram1D {
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public:
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Histogram1D(const size_t no_bins, const float min_value, const float max_value, const std::vector<t_gfh> &gfh);
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float getBinWidth();
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size_t getBinCount();
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void selectByUniformnessMaximization();
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void selectByUniformnessMaximization(float &entropy);
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void selectByNormMaximization();
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void selectByNormMaximization(float &entropy);
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t_indices getSelectedIndices();
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private:
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size_t _no_bins;
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size_t _point_count_remaining;
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size_t _point_count_selected;
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size_t _bin_sel_ptr;
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float _bin_width;
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float _val_min;
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float _val_max;
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// vector (size: number of bins) of vectors of pairs (first: index in original cloud; second: value) sorted in descending order by pair value
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std::vector<std::vector<t_gfh>> _counts_remaining;
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std::vector<std::vector<t_gfh>> _counts_selected;
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void construct(const std::vector<t_gfh> &gfh);
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size_t getBin(const float point);
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std::vector<float> estimatePDF();
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float computeEntropy(const std::vector<float> &pdf);
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};
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//}
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} // namespace rms

‎include/rms/rms.h‎

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#include <ros/ros.h>
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#include <pcl/point_types.h>
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#include <pcl/point_cloud.h>
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#include <pcl/kdtree/kdtree_flann.h>
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#include <pcl/filters/voxel_grid.h>
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#include <pcl_conversions/pcl_conversions.h>
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#include <sensor_msgs/PointCloud2.h>
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#include <sensor_msgs/point_cloud2_iterator.h>
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#include <mrs_lib/param_loader.h>
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#include <mrs_lib/scope_timer.h>
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#include <rms/histogram.h>
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namespace rms
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{
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/* //{ class RMS */
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using t_points = pcl::PointCloud<pcl::PointXYZ>::Ptr;
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using t_voxel = Eigen::Vector3i;
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class RMS {
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// | ---------------------- Voxelization ---------------------- |
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struct VoxelHash
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{
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size_t operator()(const t_voxel& voxel) const {
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const std::uint32_t* vec = reinterpret_cast<const uint32_t*>(voxel.data());
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return ((1 << 20) - 1) & (vec[0] * 73856093 ^ vec[1] * 19349663 ^ vec[2] * 83492791);
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}
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};
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// | ----------------------- Public API ----------------------- |
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public:
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RMS(mrs_lib::ParamLoader& param_loader);
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void sample(sensor_msgs::PointCloud2::Ptr& msg_inout);
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// | --------------- ROS and conversion methods --------------- |
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private:
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void fromROSMsg(const sensor_msgs::PointCloud2::Ptr cloud, t_points& pcl_cloud);
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void extractByIndices(sensor_msgs::PointCloud2::Ptr& msg_inout, t_indices& indices);
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// | ---------------- RMS variables and methods --------------- |
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private:
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size_t _K = 10;
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float _lambda = 1.0f;
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float _voxel_input = -1.0f;
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float _voxel_output = -1.0f;
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void voxelizeIndices(const float voxel_size, const t_points pc_in, t_indices& indices_inout, const bool check_NaNs = true);
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std::vector<t_gfh> computeGFH(const t_points points, const t_indices& indices);
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t_indices sampleByGFH(const t_points points, const std::vector<t_gfh>& gfh, const size_t K, const float lambda);
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};
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//}
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} // namespace rms

‎launch/rms_nodelet.launch‎

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<launch>
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<arg name="NS" default="$(optenv UAV_NAME)" />
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<arg name="standalone" default="true" />
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<arg name="debug" default="false" />
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<arg name="custom_config" default="" />
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<arg name="node_name" default="rms_nodelet" />
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<arg name="name_postfix" default="" />
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<!-- Inputs -->
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<arg name="points_in" default="/$(arg NS)/os_cloud_nodelet/points_processed" />
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<!-- Outputs -->
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<arg name="points_out" default="$(arg points_in)_filtered" />
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<!-- Debug? -->
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<arg if="$(arg debug)" name="launch_prefix" value="valgrind --tool=callgrind" />
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<arg unless="$(arg debug)" name="launch_prefix" value="" />
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<!-- Standalone? -->
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<arg if="$(eval arg('standalone') or arg('debug'))" name="nodelet" value="standalone" />
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<arg if="$(eval arg('standalone') or arg('debug'))" name="nodelet_manager" value="" />
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<!-- Nodeleted? -->
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<arg name="nodelet_manager_name" default="$(arg NS)_rms_nodelet_manager" />
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<arg if="$(eval not arg('standalone') and not arg('debug'))" name="nodelet" value="load" />
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<arg if="$(eval not arg('standalone') and not arg('debug'))" name="nodelet_manager" value="$(arg nodelet_manager_name)" />
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<!-- Postfix? -->
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<arg if="$(eval arg('name_postfix') == '')" name="nodelet_name" value="$(arg node_name)" />
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<arg unless="$(eval arg('name_postfix') == '')" name="nodelet_name" value="$(arg node_name)_$(arg name_postfix)" />
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<group ns="$(arg NS)">
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<node pkg="nodelet" type="nodelet" name="$(arg nodelet_name)" args="$(arg nodelet) rms/RMSNodelet $(arg nodelet_manager)" output="screen" launch-prefix="$(arg launch_prefix)">
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<rosparam file="$(find rms)/config/default.yaml" command="load" />
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<rosparam if="$(eval not arg('custom_config') == '')" file="$(arg custom_config)" command="load" />
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<!-- Subscribers -->
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<remap from="~points_in" to="$(arg points_in)" />
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<!-- Publishers -->
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<remap from="~points_out" to="$(arg points_out)" />
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</node>
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</group>
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</launch>

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