ultra96v2上でorb_slam2をtum datasetで動作させてみた話

ultra96v2上でorb_slam2のaccelerationを行う前に、 評価のためのtum datasetを準備して使ってみた話。

環境

• ubuntu:20.04
• vitis:2020.2
• yocto:zeus(https://github.com/akira-nishiyama/petalinux-ros2-manifests feature-v2020.2ブランチ)
• board:ultra96v2(https://github.com/akira-nishiyama/ultra96v2_4z.git feature-v2020.2ブランチ)

準備

vivadoプロジェクト(これまでから変更なし)

source <vivado_installation_path>/setup.sh
source ~/vivado_cmake_helper/setup.sh
https://github.com/akira-nishiyama/ultra96v2_4z.git -b feature-v2020.2
cd ultra96v2_4z
mkdir build
cd build
cmake .. -DCMAKE_INSTALL_PREFIX=~/<xsa-path> -GNinja
cmake --build .
ninja install

petalinux(tum datasetを/home/rootに追加。emulationの簡素化のため)

cd <petalinux-project-path>
repo init -u http://github.com/akira-nishiyama/petalinux-ros2-manifests -b feature-rel-v2020.2
repo sync

local.confを変更してxsaを指定する

HDF_EXT_ultra96v2-zynqmp = "xsa"
HDF_BASE_ultra96v2-zynqmp = "file://"
HDF_PATH_ultra96v2-zynqmp = "<xsa-file-path>/<yourdesign.xsa>"
QB_TAP_OPT_forcevariable = "-netdev tap,id=net0,ifname=tap0"

cd <petalinux-project-path>
source setupsdk
MACHINE=ultra96v2-zynqmp bitbake petalinux-image-minimal-ultra96v2ros2
MACHINE=ultra96v2-zynqmp bitbake petalinux-image-minimal-ultra96v2ros2 -c do_populate_sdk
tmp/deploy/sdk/petalinux-glibc-x86_64-petalinux-image-minimal-ultra96v2ros2-aarch64-ultra96v2-zynqmp-toolchain-2020.2.sh -d <sdk-installation-path>

<sdk-installation-path>/sysroots/x86_64-petalinux-linux/usr/share/cmake/OEToolchainConfig.cmakeを次の通り編集する

set( CMAKE_FIND_ROOT_PATH "\$ENV{OECORE_TARGET_SYSROOT};\$ENV{OECORE_NATIVE_SYSROOT}" )

<sdk-installation-path>sysroots/aarch64-xilinx-linux/usr/share/fastrtps/cmake/fastrtps-targets.cmakeを修正する。

set_target_properties(fastrtps PROPERTIES
  INTERFACE_INCLUDE_DIRECTORIES "${_IMPORT_PREFIX}/include"
  INTERFACE_LINK_LIBRARIES "fastcdr;foonathan_memory;-lpthread;dl;$ENV{OECORE_TARGET_SYSROOT}/usr/lib/libtinyxml2.so;\$<\$<BOOL:1>:OpenSSL::SSL\$<SEMICOLON>OpenSSL::Crypto>;\$<\$<BOOL:>:iphlpapi\$<SEMICOLON>Shlwapi>"
)

sw_emu

build

git clone https://github.com/akira-nishiyama/orb_slam_2_ros.git -b feature-fpga
source <vitis-installation-path>/settings64.sh
source <sdk-installation-path>/environment-setup-aarch64-xilinx-linux
export AMENT_PREFIX_PATH=$OECORE_NATIVE_SYSROOT/usr:$OECORE_TARGET_SYSROOT/usr
export PYTHONPATH=$OECORE_NATIVE_SYSROOT/usr/lib/python3.7/site-packages:$OECORE_TARGET_SYSROOT/usr/lib/python3.7/site-packages
cmake .. -DCMAKE_INSTALL_SO_NO_EXE=0 -DBUILD_TESTING=OFF -DCMAKE_NO_SYSTEM_FROM_IMPORTED=1 -GNinja -DCMAKE_INSTALL_PREFIX=<path-to-sd-card-root>/usr -DPLATFORM_COMPONENTS_PATH=<path-to-platform-components> -DBUILD_TEST_TARGETS=ON -DBUILD_TARGET=sw_emu
ninja -j4

run

エミュレータを起動する

cd hw/hw_link/package_sw_emu/
source /opt/Xilinx/Vitis/2020.2/settings64.sh
./launch_sw_emu.sh -pid-file emulation.pid -no-reboot -forward-port 1440 1534 -forward-port 2222 22

テストプログラムを/home/rootに転送する

scp -P 2222 ./orb_slam2_ros_mono_tum_test root@localhost:/home/root

ultra96上でテストプログラムを実行する

./orb_slam2_ros_mono_tum_test /usr/share/orb_slam2_ros/orb_slam2/Vocabulary/ORBvoc.txt ./tum-dataset/

result

ログは以下の通り。遅いせいかKeyFrameが全然認識できていない。 実機の評価は別の機会にしてopencl化して改善できるかはこれから試す。

ORB-SLAM2 Copyright (C) 2014-2016 Raul Mur-Artal, University of Zaragoza.
This program comes with ABSOLUTELY NO WARRANTY;
This is free software, and you are welcome to redistribute it
under certain conditions. See LICENSE.txt.

OpenCV version : 3.4.3
Major version : 3
Minor version : 4
Subminor version : 3
Input sensor was set to: Monocular

Loading ORB Vocabulary.
Vocabulary loaded!


Camera Parameters: 
- fx: 517.306
- fy: 516.469
- cx: 318.643
- cy: 255.314
- k1: 0.262383
- k2: -0.953104
- k3: 0.002628
- p1: 1.16331
- p2: -0.005358
- fps: 30
- bf: 0
- color order: RGB (ignored if grayscale)

ORB Extractor Parameters: 
- Number of Features: 1000
- Scale Levels: 8
- Scale Factor: 1.2
- Initial Fast Threshold: 20
- Minimum Fast Threshold: 7

-------
Start processing sequence ...
Images in the sequence: 798

-------

median tracking time: 1.5039
mean tracking time: 1.74812

Saving keyframe trajectory to KeyFrameTrajectory.txt ...

trajectory saved!