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‎CMakeLists.txt

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cmake_minimum_required(VERSION 2.8)
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project(Jetson-SLAM)
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IF(NOT CMAKE_BUILD_TYPE)
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SET(CMAKE_BUILD_TYPE Release)
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ENDIF()
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MESSAGE("Build type: " ${CMAKE_BUILD_TYPE})
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set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -Wall -O3 -march=native ")
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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wall -O3 -march=native")
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# Check C++11 or C++0x support
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include(CheckCXXCompilerFlag)
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CHECK_CXX_COMPILER_FLAG("-std=c++11" COMPILER_SUPPORTS_CXX11)
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CHECK_CXX_COMPILER_FLAG("-std=c++0x" COMPILER_SUPPORTS_CXX0X)
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if(COMPILER_SUPPORTS_CXX11)
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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
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add_definitions(-DCOMPILEDWITHC11)
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message(STATUS "Using flag -std=c++11.")
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elseif(COMPILER_SUPPORTS_CXX0X)
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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++0x")
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add_definitions(-DCOMPILEDWITHC0X)
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message(STATUS "Using flag -std=c++0x.")
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else()
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message(FATAL_ERROR "The compiler ${CMAKE_CXX_COMPILER} has no C++11 support. Please use a different C++ compiler.")
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endif()
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find_package(CUDA REQUIRED)
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LIST(APPEND CMAKE_MODULE_PATH ${PROJECT_SOURCE_DIR}/cmake_modules)
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find_package(OpenCV 3.0 QUIET)
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if(NOT OpenCV_FOUND)
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message(FATAL_ERROR "OpenCV >= 3 not found.")
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endif()
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find_package(Eigen3 3.1.0 REQUIRED)
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find_package(Pangolin REQUIRED)
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include_directories(
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${PROJECT_SOURCE_DIR}
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${PROJECT_SOURCE_DIR}/include
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${EIGEN3_INCLUDE_DIR}
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${Pangolin_INCLUDE_DIRS}
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${CUDA_INCLUDE_DIRS}
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)
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set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${PROJECT_SOURCE_DIR}/lib)
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cuda_add_library(${PROJECT_NAME} SHARED
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src/Converter.cc
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src/Frame.cc
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src/FrameDrawer.cc
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src/Initializer.cc
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src/KeyFrame.cc
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src/KeyFrameDatabase.cc
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src/LocalMapping.cc
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src/LoopClosing.cc
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src/Map.cc
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src/MapDrawer.cc
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src/MapPoint.cc
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src/Optimizer.cc
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src/ORBextractor.cc
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src/ORBmatcher.cc
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src/PnPsolver.cc
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src/Sim3Solver.cc
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src/System.cc
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src/Tracking.cc
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src/Viewer.cc
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src/cuda/orb_bitpattern.cpp
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src/cuda/orb_copy_output.cu
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src/cuda/orb_descriptor.cu
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src/cuda/orb_FAST_apply_NMS_G.cu
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src/cuda/orb_FAST_apply_NMS_L.cu
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src/cuda/orb_FAST_apply_NMS_MS.cpp
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src/cuda/orb_FAST_apply_NMS_MS.cu
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src/cuda/orb_FAST_compute_score.cu
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src/cuda/orb_FAST_obtain_keypoints.cpp
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src/cuda/orb_FAST_orientation.cu
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src/cuda/orb_gaussian.cu
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src/cuda/orb_gpu.cpp
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src/cuda/orb_matcher.cu
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src/cuda/orb_pyramid.cu
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src/cuda/orb_stereo_match.cu
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src/cuda/synced_mem_holder.cpp
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src/cuda/tracking_isinfrustum.cu
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)
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target_link_libraries(${PROJECT_NAME}
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${OpenCV_LIBS}
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${EIGEN3_LIBS}
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${Pangolin_LIBRARIES}
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${CUDA_LIBRARIES}
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${CUDA_CUBLAS_LIBRARIES}
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${PROJECT_SOURCE_DIR}/Thirdparty/DBoW2/lib/libDBoW2.so
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${PROJECT_SOURCE_DIR}/Thirdparty/g2o/lib/libg2o.so
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)
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# Build execs
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set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${PROJECT_SOURCE_DIR}/execs)
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add_executable(stereo_kitti execs/stereo_kitti.cc)
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target_link_libraries(stereo_kitti ${PROJECT_NAME})
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add_executable(stereo_euroc execs/stereo_euroc.cc)
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target_link_libraries(stereo_euroc ${PROJECT_NAME})
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add_executable(stereo_kaistvio execs/stereo_kaistvio.cc)
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target_link_libraries(stereo_kaistvio ${PROJECT_NAME})
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add_executable(stereo_live execs/stereo_live.cpp)
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target_link_libraries(stereo_live ${PROJECT_NAME})
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‎README.md

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# Jetson-SLAM
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**More updates coming soon**
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**To be done:**
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1. Update exec folder
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**The frontend of Jetson-SLAM will be released as a separate repository as-well.**
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**Authors:** Ashish Kumar
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![Jetson-SLAM Design](/assets/img/jetson-slam.png "Jetson-SLAM")
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This repository contains Jetson-SLAM with [FULL-BA back-end](https://128.84.21.199/pdf/1610.06475.pdf)
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Jetson-SLAM is a GPU-thrusted real-time SLAM library for **Monocular**, **Stereo** and **RGB-D** cameras. It can run very high speeds beyond **500FPS** on RTX-2070 and Beyond **90FPS** on Jetson-NX **@320x240** resolution. Please see the [Jetson-SLAM Paper](https://drive.google.com/file/d/1KagYH0YVSDOeBwv4oHyKrmndOF7Sc_TV/view?usp=drive_link) for rigorous results over different resolutions, GPUs and comparison with existing VO/VIO/SLAM pipelines.
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**Jetson-SLAM can run alongside Deep Neural Networks. It is fully behchmarked with VGG**
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# Video
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<p align="center">
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<a href="https://drive.google.com/file/d/16FN0FKy76R6MBdu44WzHyH3KstruOeJT/view?usp=drive_link" target="_blank" ><img align="center" src="/assets/img/video_thumbnail.png"
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alt="Jetson-SLAM" width="70%" height="70%" border="0" /></a>
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</p>
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<div>
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<p align="center">
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<img align="center" src="/assets/gif/kaistvio_circle.gif"
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alt="Jetson-SLAM" width="50%" height="50%" border="0" />
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</p>
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# Main Highlight
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<p align="center">
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<img align="center" src="/assets/img/fig1.png"
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alt="Jetson-SLAM" width="70%" height="70%" border="0" />
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# 1. Main Results
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### Datasets
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1. [KITTI-Benchmark](https://github.com/zinuok/VINS-MONO)
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2. [EuRoC Benchmark](https://projects.asl.ethz.ch/datasets/doku.php?id=kmavvisualinertialdatasets)
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3. [KAIST-VIO Benchmark](https://github.com/url-kaist/kaistviodataset)
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#### Results on KITTI Benchmark
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![Results on KITTI Benchmark](/assets/img/kitti_plot.png)
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![KITTI Trajectories](/assets/img/kitti_traj.png)
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#### Results on EuRoC Benchmark
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![Results on EuRoC Benchmark](/assets/img/euroc_plot.png)
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![Results on EuRoC Benchmark](/assets/img/euroc_table.png)
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![EuRoC Trajectories](/assets/img/euroc_traj.png)
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#### Results on KAIST-VIO Benchmark
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![Results on KAIST-VIO Benchmark](/assets/img/kaistvio_table.png)
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![KAIST-VIO Trajectories](/assets/img/kaistvio_traj.png)
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#### Performance with scaled versions of VGG-16 Co-existing on Jetson-NX
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![Co-exating VGG performance](/assets/img/vgg.png)
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### Build Instructions
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**Step-1**
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Install the dependencies given below:
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1. OpenCV 3
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2. Eigen3
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3. CUDA
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4. Pangolin
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**Step-2**
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Run build.sh
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### Run Instructions
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Go to execs and run Jetson-SLAM on following choices:
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1. Run stereo_kitti for KITTI-Benchmark
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2. Run stereo_euroc for EuRoC Benchmark
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3. Run stereo_kaistvio for KAIST-VIO Benchmark
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4. Run stereo_live for live images from a Stereo-Rig. Please customize the "stereo_live_config.yaml" file for your stereo rig.
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### License
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Jetson-SLAM is released under a [GPLv3 license].
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### Bibtex citation:
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@article{Jetson-SLAM,
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title={{High-Speed Stereo Visual-{SLAM} For Low-Powered Computing Devices},
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author={Kumar, Ashish and Park, Jaesik and Behera, Laxmidhar},
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year={2023},
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}
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‎Thirdparty/DBoW2/CMakeLists.txt

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cmake_minimum_required(VERSION 2.8)
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project(DBoW2)
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set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -Wall -O3 -march=native ")
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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wall -O3 -march=native")
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set(HDRS_DBOW2
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DBoW2/BowVector.h
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DBoW2/FORB.h
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DBoW2/FClass.h
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DBoW2/FeatureVector.h
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DBoW2/ScoringObject.h
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DBoW2/TemplatedVocabulary.h)
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set(SRCS_DBOW2
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DBoW2/BowVector.cpp
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DBoW2/FORB.cpp
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DBoW2/FeatureVector.cpp
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DBoW2/ScoringObject.cpp)
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set(HDRS_DUTILS
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DUtils/Random.h
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DUtils/Timestamp.h)
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set(SRCS_DUTILS
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DUtils/Random.cpp
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DUtils/Timestamp.cpp)
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find_package(OpenCV 3.0 QUIET)
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if(NOT OpenCV_FOUND)
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find_package(OpenCV 2.4.3 QUIET)
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if(NOT OpenCV_FOUND)
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message(FATAL_ERROR "OpenCV > 2.4.3 not found.")
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endif()
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endif()
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set(LIBRARY_OUTPUT_PATH ${PROJECT_SOURCE_DIR}/lib)
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include_directories(${OpenCV_INCLUDE_DIRS})
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add_library(DBoW2 SHARED ${SRCS_DBOW2} ${SRCS_DUTILS})
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target_link_libraries(DBoW2 ${OpenCV_LIBS})
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‎Thirdparty/DBoW2/DBoW2/BowVector.cpp

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/**
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* File: BowVector.cpp
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* Date: March 2011
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* Author: Dorian Galvez-Lopez
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* Description: bag of words vector
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* License: see the LICENSE.txt file
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*
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*/
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#include <iostream>
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#include <fstream>
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#include <vector>
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#include <algorithm>
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#include <cmath>
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#include "BowVector.h"
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namespace DBoW2 {
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// --------------------------------------------------------------------------
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BowVector::BowVector(void)
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{
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}
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// --------------------------------------------------------------------------
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BowVector::~BowVector(void)
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{
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}
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// --------------------------------------------------------------------------
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void BowVector::addWeight(WordId id, WordValue v)
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{
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BowVector::iterator vit = this->lower_bound(id);
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if(vit != this->end() && !(this->key_comp()(id, vit->first)))
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{
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vit->second += v;
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}
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else
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{
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this->insert(vit, BowVector::value_type(id, v));
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}
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}
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// --------------------------------------------------------------------------
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void BowVector::addIfNotExist(WordId id, WordValue v)
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{
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BowVector::iterator vit = this->lower_bound(id);
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if(vit == this->end() || (this->key_comp()(id, vit->first)))
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{
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this->insert(vit, BowVector::value_type(id, v));
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}
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}
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// --------------------------------------------------------------------------
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void BowVector::normalize(LNorm norm_type)
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{
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double norm = 0.0;
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BowVector::iterator it;
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if(norm_type == DBoW2::L1)
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{
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for(it = begin(); it != end(); ++it)
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norm += fabs(it->second);
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}
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else
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{
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for(it = begin(); it != end(); ++it)
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norm += it->second * it->second;
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norm = sqrt(norm);
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}
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if(norm > 0.0)
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{
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for(it = begin(); it != end(); ++it)
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it->second /= norm;
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}
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}
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// --------------------------------------------------------------------------
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std::ostream& operator<< (std::ostream &out, const BowVector &v)
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{
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BowVector::const_iterator vit;
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std::vector<unsigned int>::const_iterator iit;
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unsigned int i = 0;
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const unsigned int N = v.size();
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for(vit = v.begin(); vit != v.end(); ++vit, ++i)
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{
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out << "<" << vit->first << ", " << vit->second << ">";
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if(i < N-1) out << ", ";
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}
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return out;
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}
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// --------------------------------------------------------------------------
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void BowVector::saveM(const std::string &filename, size_t W) const
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{
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std::fstream f(filename.c_str(), std::ios::out);
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WordId last = 0;
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BowVector::const_iterator bit;
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for(bit = this->begin(); bit != this->end(); ++bit)
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{
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for(; last < bit->first; ++last)
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{
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f << "0 ";
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}
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f << bit->second << " ";
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last = bit->first + 1;
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}
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for(; last < (WordId)W; ++last)
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f << "0 ";
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f.close();
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}
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// --------------------------------------------------------------------------
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} // namespace DBoW2
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