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VINS-RGBD-FAST

VINS-RGBD-FAST is a SLAM system based on VINS-RGBD. We do some refinements to accelerate the system's performance in resource-constrained embedded paltform, like HUAWEI Atlas200 DK, NVIDIA Jetson AGX Xavier.

Refinements

  • grid-based feature detection
  • extract FAST feature instead of Harris feature
  • added stationary initialization
  • added IMU-aided feature tracking
  • added extracted-feature area's quality judgement
  • solved feature clusttering problem result frome FAST feature
  • use "sensor_msg::CompressedImage" as image topic type

Related Paper:

@ARTICLE{9830851,  
  author={Liu, Jianheng and Li, Xuanfu and Liu, Yueqian and Chen, Haoyao},  
  journal={IEEE Robotics and Automation Letters},  
  title={RGB-D Inertial Odometry for a Resource-Restricted Robot in Dynamic Environments},   
  year={2022},  
  volume={7},  
  number={4},  
  pages={9573-9580},  
  doi={10.1109/LRA.2022.3191193}}

RGBD-Inertial Trajectory Estimation and Mapping for Small Ground Rescue Robot

Based one open source SLAM framework VINS-Mono.

The approach contains

  • Depth-integrated visual-inertial initialization process.
  • Visual-inertial odometry by utilizing depth information while avoiding the limitation is working for 3D pose estimation.
  • Noise elimination map which is suitable for path planning and navigation.

However, the proposed approach can also be applied to other application like handheld and wheeled robot.

1. Prerequisites

1.1. Ubuntu 16.04 or 18.04.

1.2. ROS version Kinetic or Melodic fully installation

1.3. Ceres Solver Follow Ceres Installation

1.4. Sophus

  git clone http://github.com/strasdat/Sophus.git
  git checkout a621ff

1.3. Atlas 200 DK环境配置

https://blog.csdn.net/qq_42703283/article/details/110389270

1.4. ROS多机通信

[https://blog.csdn.net/qq_42703283/article/details/110408848](

2. Datasets

Recording by RealSense D435i. Contain 9 bags in three different applicaions:

Note the rosbags are in compressed format. Use "rosbag decompress" to decompress.

Topics:

  • depth topic: /camera/aligned_depth_to_color/image_raw
  • color topic: /camera/color/image_raw
  • imu topic: /camera/imu

我们使用的是压缩图像节点：

  • depth topic: /camera/aligned_depth_to_color/image_raw
  • color topic: /camera/color/image_raw/compressed
  • imu topic: /camera/imu

如何录制一个数据包

  1. 运行d435i
  2. rosbag record /camera/imu /camera/color/image_raw /camera/aligned_depth_to_color/image_raw /camera/color/camera_info /camera/color/image_raw/compressed

3. Run with Docker

make Dockerfile like below

FROM ros:melodic-ros-core-bionic

# apt-get update
RUN apt-get update

# install essentials
RUN apt install -y gcc
RUN apt install -y g++
RUN apt-get install -y cmake
RUN apt-get install -y wget
RUN apt install -y git

# install ceres
WORKDIR /home
RUN apt-get install -y libgoogle-glog-dev libgflags-dev
RUN apt-get install -y libatlas-base-dev
RUN apt-get install -y libeigen3-dev
RUN apt-get install -y libsuitesparse-dev
RUN wget http://ceres-solver.org/ceres-solver-2.1.0.tar.gz
RUN tar zxf ceres-solver-2.1.0.tar.gz
WORKDIR /home/ceres-solver-2.1.0
RUN mkdir build
WORKDIR /home/ceres-solver-2.1.0/build
RUN cmake ..
RUN make
RUN make install

# install sophus
WORKDIR /home
RUN git clone https://github.com/demul/Sophus.git
WORKDIR /home/Sophus
RUN git checkout fix/unit_complex_eror
RUN mkdir build
WORKDIR /home/Sophus/build
RUN cmake ..
RUN make
RUN make install

# install ros dependencies
WORKDIR /home
RUN mkdir ros_ws
WORKDIR /home/ros_ws
RUN apt-get -y install ros-melodic-cv-bridge
RUN apt-get -y install ros-melodic-nodelet
RUN apt-get -y install ros-melodic-tf
RUN apt-get -y install ros-melodic-image-transport
RUN apt-get -y install ros-melodic-rviz

# build vins-rgbd-fast
RUN mkdir src
WORKDIR /home/ros_ws/src
RUN git clone https://github.com/jianhengLiu/VINS-RGBD-FAST
WORKDIR /home/ros_ws
RUN /bin/bash -c ". /opt/ros/melodic/setup.bash; cd /home/ros_ws; catkin_make"
RUN echo "source /home/ros_ws/devel/setup.bash" >> ~/.bashrc

docker build .

4. Licence

The source code is released under GPLv3 license.