Can't build from source : WifiSignalSubNode.cpp undefined reference to rtabmap::util3d::transformPointCloud

[GiannisSp]

I am trying to build rtabmap & rtabmap-ros from source, because I want CUDA support RTAB map docker, that for now I'm testing it on native Ubuntu20.04. As far as rtabmap everything works, without building errors.
RTABmap & RTABmap-ros version 0.21.5-noetic
VTK version 9.4 ( tried 7.1 too )
PCL version 1.14.1 (without the -march=native flag)(tried down to 1.11) [ can't test 1.10 'cause I don't have the right GPU ]
Boost version 1.71
OpenCV version : latest 4.x
ROS : Noetic , Ubuntu 20.04 (docker)
Tried different GCC/G++ [ v11, v8 ]

Any help would be much appreciated. I've struggled for days on these and past problems
Note: I am not planning to use directly WiFi capabilities (if any), so disabling(bypassing) this, may still suffice

Error code : while running catkin_make -j1 from "catkin_ws" folder

[ 66%] Linking CXX executable /home/catkin_ws/devel/lib/rtabmap_demos/wifi_signal_sub
/usr/bin/ld: warning: libpcl_io.so.1.14, needed by /usr/local/lib/librtabmap_core.so.0.21.8, may conflict with libpcl_io.so.1.10
/usr/bin/ld: CMakeFiles/rtabmap_wifi_signal_sub.dir/src/WifiSignalSubNode.cpp.o: in function `mapDataCallback(boost::shared_ptr<rtabmap_msgs::MapData_<std::allocator<void> > const> const&)':
WifiSignalSubNode.cpp:(.text+0x15e2): undefined reference to `rtabmap::util3d::transformPointCloud(boost::shared_ptr<pcl::PointCloud<pcl::PointXYZRGB> > const&, rtabmap::Transform const&)'
collect2: error: ld returned 1 exit status
make[2]: *** [rtabmap_ros/rtabmap_demos/CMakeFiles/rtabmap_wifi_signal_sub.dir/build.make:545: /home/catkin_ws/devel/lib/rtabmap_demos/wifi_signal_sub] Error 1
make[1]: *** [CMakeFiles/Makefile2:6886: rtabmap_ros/rtabmap_demos/CMakeFiles/rtabmap_wifi_signal_sub.dir/all] Error 2
make: *** [Makefile:146: all] Error 2
Invoking "make -j1" failed

Dockerfile code

FROM nvidia/cuda:12.2.0-base-ubuntu20.04
ENV DEBIAN_FRONTEND=noninteractive

ARG depfolder=/home/

WORKDIR ${depfolder}


RUN apt update -y; \
    apt install -y build-essential wget  curl python3 python3-dev libxml2 nano git \ 
                    python3 python3-pip python3-dev python3-setuptools gfortran; 

#################
##### Install CMake  22
#################
RUN apt install -y libxrandr-dev libxinerama-dev libxi-dev libssl-dev; apt remove --purge cmake; hash -r;
RUN git clone https://github.com/Kitware/CMake.git; cd CMake; ./bootstrap && make -j60 && make install; cd ..


#cuSPARSELt
RUN apt install -y libcusparselt0 libcusparselt-dev


RUN wget -q https://developer.download.nvidia.com/compute/cuda/12.2.0/local_installers/cuda_12.2.0_535.54.03_linux.run
RUN sh cuda_12.2.0_535.54.03_linux.run --toolkit --silent
ENV LD_LIBRARY_PATH=/usr/local/cuda/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
ENV PATH=/usr/local/cuda/bin${PATH:+:${PATH}}
RUN ldconfig 

# check the appropriate package based on ubuntu version (20 vs 22)
RUN wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-keyring_1.1-1_all.deb -q
RUN echo "deb [signed-by=/usr/share/keyrings/cuda-archive-keyring.gpg] https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/ /" > /etc/apt/sources.list.d/cuda.list
RUN dpkg -i cuda-keyring_1.1-1_all.deb
RUN apt-get update -q
RUN apt-get -y install cudnn-cuda-12

# #direct FWWT to cuWWT if compatible
ENV LD_PRELOAD=/usr/local/cuda/lib64/libcufft.so

# ################
# ## LAPACK install
# ################
RUN git clone https://github.com/Reference-LAPACK/lapack.git; \
    cd lapack; \
    mkdir build; \
    cd build; \
    cmake .. -DUSE_OPTIMIZED_LAPACK=ON; \
    cmake --build . -j60 --target install

# ################
# ## Eigen install
# ################

RUN apt install -y software-properties-common; apt-get update -y; \
        apt install -y libblas-dev liblz4-dev pkg-config liblz4-dev; \
        \
        add-apt-repository -y ppa:ubuntu-toolchain-r/test

RUN wget -qO- https://gitlab.com/libeigen/eigen/-/archive/3.3.7/eigen-3.3.7.tar.gz | tar xz; \
    cd eigen-3.3.7; mkdir build; cd build; \
    cmake .. -D  EIGEN_TEST_CUDA=ON; make -j58; make install; cd ../..
	

# ################
# ## FLANN install 
# ################

RUN git clone https://github.com/flann-lib/flann.git; cd flann; git pull origin  master; \
    mkdir build; cd build; \
    cmake .. -DCMAKE_BUILD_TYPE=Release -DBUILD_CUDA_LIB=ON ; make -j58; make install; cd ../..


RUN apt install libmpfr-dev libgmp-dev -y
RUN apt update; apt install -y  gcc-11 g++-11 
RUN apt -y update; update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-11 100; apt -y update
RUN update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-11 100


# ################
# ## SuiteSparse install  # cuda flags on , by default on cmake 
# ################
# RUN apt-get install gfortran-7
RUN git clone https://github.com/DrTimothyAldenDavis/SuiteSparse.git; cd SuiteSparse; git checkout stable; git pull origin  stable; \
    mkdir build; cd build; 
RUN apt install -y libopenblas-dev 
RUN cmake .. -DCMAKE_BUILD_TYPE=Release; make -j4; make install; cd ../..



# ###############
# # Boost Install 
# ###############

RUN wget https://boostorg.jfrog.io/artifactory/main/release/1.71.0/source/boost_1_71_0.tar.bz2; tar -xjf boost_1_71_0.tar.bz2
RUN apt-get install build-essential \
    g++ \
    gcc \
    python3-dev \
    python3-pip \
    libicu-dev \
    libbz2-dev \
    libssl-dev \
    libboost-all-dev \
    wget -y
RUN cd boost_1_71_0; ./bootstrap.sh --with-libraries=all
ENV PATH=/usr/local/cuda/bin:$PATH
ENV CUDADIR=/usr/local/cuda
RUN cd boost_1_71_0; ./b2; \ 
./b2 install --prefix=/usr/local/boost toolset=gcc cxxflags="-D__CUDACC__" --cuda=nvcc; cd ..
# RUN ./b2 install --prefix=/usr/local/boost
ENV BOOST_ROOT=/usr/local/boost
ENV CPLUS_INCLUDE_PATH="\${BOOST_ROOT}/include:\$CPLUS_INCLUDE_PATH"
ENV LIBRARY_PATH="\${BOOST_ROOT}/lib:\$LIBRARY_PATH"

# # ###############
# # ## VTK install
# # ###############

RUN git clone --recursive https://gitlab.kitware.com/vtk/vtk.git vtk/source; cd vtk/source; git checkout master git pull origin master; \
    cd ..; mkdir build
RUN cd vtk/build; \
 cmake ../source -DCMAKE_BUILD_TYPE=Release -DVTK_USE_CUDA=ON -DVTK_GROUP_ENABLE_Qt=NO -DVTK_MODULE_ENABLE_VTK_GUISupportQtQuick=NO -DVTK_MODULE_ENABLE_VTK_GUISupportQtSQL=NO -DVTK_MODULE_ENABLE_VTK_RenderingOpenVR=NO -DVTK_MODULE_ENABLE_VTK_RenderingRayTracing=NO -DVTK_MODULE_ENABLE_VTK_RenderingVR=NO -D CMAKE_VERBOSE_MAKEFILE=ON; \
 make -j20; make install
# for vtk 7.1
# RUN apt update -y; apt install libvtk7-dev -y

#############
## OPENCV for CUDA
############

RUN apt install cmake gcc g++ python3 python3-dev python3-numpy libavcodec-dev libavformat-dev libswscale-dev -y
RUN apt install -y libgstreamer-plugins-base1.0-dev libgstreamer1.0-dev libgtk-3-dev libpng-dev libjpeg-dev libopenexr-dev libtiff-dev libwebp-dev
RUN git clone https://github.com/opencv/opencv.git;\
    git clone https://github.com/opencv/opencv_contrib.git
RUN cd opencv; mkdir build; cd build; \ 
    cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D WITH_CUDA=ON -D WITH_CUDNN=ON -D WITH_CUBLAS=ON -DCUDA_SDK_ROOT_DIR=/usr/local/cuda -D OPENCV_DNN_CUDA=ON -D CUDA_ARCH_BIN=8.6 -D OPENCV_EXTRA_MODULES_PATH=../../opencv_contrib/modules -D HAVE_opencv_python3=ON -DCMAKE_CUDA_ARCHITECTURES="86" -DCUDA_FAST_MATH=ON -DLAPACK_INCLUDE_DIR=/home/lapack/build/include -DLAPACK_LIBRARIES=/home/lapack/build/lib ..
RUN cd opencv/build; make -j50; make install; ldconfig
# #use appropriate python version  
RUN ln -s /usr/local/lib/python3.8/site-packages/cv2 /usr/local/lib/python3.8/dist-packages/cv2 

# #############
# # PCL install
# #############

RUN apt-get update; apt-get install libboost-all-dev libcjson-dev libpcap-dev freeglut3 freeglut3-dev libpcap-dev qt5-qmake qtbase5-dev qtchooser \
 libusb-1.0-0-dev libopenni2-dev -y 

RUN git clone https://github.com/PointCloudLibrary/pcl.git && cd pcl && git checkout pcl-1.14.1; git pull origin pcl-1.14.1
RUN cd pcl; mkdir build; cd build; \

    cmake .. -D BUILD_CUDA=ON -D BUILD_GPU=ON -D WITH_OPENGL=OFF -DBUILD_cuda_io=ON -DBUILD_gpu_surface=ON -DBUILD_gpu_tracking=ON -DWITH_QT=OFF -DCUDA_SDK_ROOT_DIR=/usr/local/cuda -DCUDA_ARCH_BIN="86"
RUN cd pcl/build; make -j58; make install

##################
# CudaSift install
##################

RUN git clone https://github.com/matlabbe/CudaSift.git 
RUN cd CudaSift; mkdir build; cd build; \
    cmake .. -DCUDA_SDK_ROOT_DIR=/usr/local/cuda; \
    make; \ 
    make install

##################
# RTABMap install
###################
# has noetic-devel
RUN git clone https://github.com/introlab/rtabmap.git; git checkout 0.21.5-noetic; git pull origin 0.21.5-noetic; \
    cd rtabmap/build; cmake .. -D WITH_CUDASIFT=ON -D WITH_QT=OFF -DCUDA_SDK_ROOT_DIR=/usr/local/cuda -D CUDA_CUDA_LIBRARY=/usr/lib/x86_64-linux-gnu/libcuda.so
RUN cd rtabmap/build; make -j58; \
    make install


#####################
# ROS1 Noetic Install
#####################
RUN sh -c 'echo "deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main" > /etc/apt/sources.list.d/ros-latest.list'
RUN apt-key adv --keyserver 'hkp://keyserver.ubuntu.com:80' --recv-key C1CF6E31E6BADE8868B172B4F42ED6FBAB17C654
RUN apt install -y python3-pip python3-setuptools python3-wheel
RUN apt update -y
RUN apt upgrade -y

RUN sh -c 'echo "deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main" > /etc/apt/sources.list.d/ros-latest.list'
RUN curl -s https://raw.githubusercontent.com/ros/rosdistro/master/ros.asc | apt-key add -
RUN apt update -y
RUN apt install ros-noetic-ros-base -y
#[inside the container-after build] 
#source /opt/ros/noetic/setup.bash
#cd catkin_ws
#catkin_make -j60;
#source devel/setup.bash

#####################
# ROS1 Rtabmap-ros 
#####################
RUN mkdir catkin_ws; cd catkin_ws; mkdir src
RUN apt install -y ros-noetic-rtabmap* ros-noetic-libg2o ros-noetic-libpointmatcher
RUN apt remove ros-noetic-rtabmap* -y; 

RUN cd catkin_ws; git clone https://github.com/introlab/rtabmap_ros.git src/rtabmap_ros; cd src/rtabmap_ros; git checkout 0.21.5-noetic; git pull origin 0.21.5-noetic
RUN cd catkin_ws/src; git clone https://github.com/ros-perception/vision_opencv.git; git checkout noetic; git pull origin noetic
#[inside the container-after build] 
#cd catkin_ws
#catkin_make -j60

Tried to clean any irrelevant code
I hope you can copy-paste without typos from my part

[matlabbe]

Maybe it is related to this warning:

/usr/bin/ld: warning: libpcl_io.so.1.14, needed by /usr/local/lib/librtabmap_core.so.0.21.8, may conflict with libpcl_io.so.1.10

As you are rebuilding everything from source, uninstall libpcl* and ros-$ROS_DISTRO-pcl* before rebuilding rtabmap

RUN apt remove ros-$ROS_DISTRO-pcl* libpcl* -y; 

You may need to rebuild pcl_ros from source too in case rtabmap_ros fails to find it.

[GiannisSp]

Thank you for your response.
If I try to remove libpcl* , it also removes the ros-$ROS_DISTRO-pcl-conversions and other vital packages. Haven't installed ros-$ROS_DISTRO-pcl and even if it gets installed silently I can see that the Makefiles target my source build installation

My workaround is to delete the older version libpcl_io.so.1.10 and create a link to libpcl_io.so.1.14 .
It didn't solve the issue.

All source builds up to RTABmap find perfectly each previous builds. That also seem to be the case with RTABmap_ros

[matlabbe]

it also removes the ros-$ROS_DISTRO-pcl-conversions and other vital packages

Yes, so you have to rebuild them from source.

Haven't installed ros-$ROS_DISTRO-pcl and even if it gets installed silently I can see that the Makefiles target my source build installation

The problem is that even if rtabmap is building against the pcl version built from source, on runtime the wrong library version can be loaded and it will just seg fault. You may verify that with ldd tool.

From experience, I've found that avoiding having the same libraries with different version installed at the same time saves a lot of issues down the road. Unless you really need latest PCL version, I would stick to the binaries to make your life easier. Note also rebuilding latest PCL on machine using c++17 by default can cause some issues. See introlab/rtabmap#1385 (comment) to set the right compile flags to avoid issues with GTSAM and g2o libraries using also Eigen library.

EDIT: just re-read original post, PCL-CUDA is not used by RTAB-Map.

[GiannisSp]

I've come with an update at last .

EDIT: just re-read original post, PCL-CUDA is not used by RTAB-Map.

So, in worst case scenario it just doesn't utilize the cuda capabilities of PCL

Update:
I've succeeded building everything from source. Instead of catkin_make I used catkin_make_isolated , for some reason it stopped building without an actual warning. I decided to skip(delete) aruco_detect from fiducials package , because I don't need it and I couldn't compile it correctly due to I had to have OpenCV <= 4.5.5 which unfortunately does not work with CUDA 12.2.

What changed:

• I made sure to remove libpcl* libopencv* libboost*
• Downloaded a bunch of packages found from ros-wiki (github) , 1/3 of them had to target ros1-devel ( ex melodic-devel, kinetic-devel , ros1) branches
  -- a few I could download with ros-noetic-<package_name> or lib<package_name>
• Made changes to CMakeLists and package.xml to include(find) std_srvs in packages that couldn't find specific header files
• Rebuild boost to actually build python_boost ( needs some extra arguments and create a user-config.jam)
• Compiled all the packages with OpenGL , QT and OpenCL = ON ( instead of turning them off , or leave them in default )
• I used the master branch of rtabmap and rtabmap_ros ( instead of checkout previous noetic release )
• made sure I'm using gcc/g++ v8

Question
If I regularly, do the following. I still do not have GPU-acellarion in nvidia-smi (I get 0% of GPU util) . I run docker with --gpu=all. Do I customize/add the nodes or something after the successful setup of rtabmap_ros ?

• play stereo_outdoorsB.bag (from ros wiki)
• roslaunch rtabmap_demos demo_stereo_outdoor.launch

Question-EDIT-1
Found out there are some gpu parameters in some nodes rosparam list | grep -i gpu and change the values to true. I have now 2 processes of total 512MB working with GPU when running
roslaunch rtabmap_demos demo_stereo_outdoor.launch regardless if I play the rosbag.

1. rtabmap_odom
2. rtabmap_slam

Is there anything else that can be done?

I will make a full guide of current releases (in the short future)

[matlabbe]

If docker is correctly using nvidia driver, rviz and rtabmap_viz should show up in nvidia-smi:

In this docker example, we launch docker with:

-e NVIDIA_VISIBLE_DEVICES=all \
-e NVIDIA_DRIVER_CAPABILITIES=all \
--runtime=nvidia \

For rtabmap_odom and rtabmap_slam, they may use CUDA if OpenCV is built with CUDA and some of those parameters are enabled/used:

rtabmap --params | grep Gpu
Param: FAST/Gpu = "false"                                  [GPU-FAST: Use GPU version of FAST. This option is enabled only if OpenCV is built with CUDA and GPUs are detected.]
Param: FAST/GpuKeypointsRatio = "0.05"                     [Used with FAST GPU.]
Param: GFTT/Gpu = "false"                                  [GPU-GFTT: Use GPU version of GFTT. This option is enabled only if OpenCV>=3 is built with CUDA and GPUs are detected.]
Param: ORB/Gpu = "false"                                   [GPU-ORB: Use GPU version of ORB. This option is enabled only if OpenCV is built with CUDA and GPUs are detected.]
Param: SIFT/Gpu = "false"                                  [CudaSift: Use GPU version of SIFT. This option is enabled only if RTAB-Map is built with CudaSift dependency and GPUs are detected.]
Param: SURF/GpuKeypointsRatio = "0.01"                     [Used with SURF GPU.]
Param: SURF/GpuVersion = "false"                           [GPU-SURF: Use GPU version of SURF. This option is enabled only if OpenCV is built with CUDA and GPUs are detected.]
Param: Stereo/Gpu = "false"                                [[Stereo/OpticalFlow=true] Enable GPU version of the optical flow approach (only available if OpenCV is built with CUDA).]
Param: Vis/CorFlowGpu = "false"                            [[Vis/CorType=1] Enable GPU version of the optical flow approach (only available if OpenCV is built with CUDA).]