VanniZhou / DWD_sensor_fusion

Lidar, camera, Radar multi-sensor fusion and Dynamic Weight Distribution (DWD) algorithm (ROS) . This project is able to fusion the targets of lidar, radar and camera, and assign them dynamic weights according to the Kalman filter effect. And make it running in ROS.

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DWD_sensor_fusion

激光雷达、摄像头、毫米波雷达多传感器融合及融合动态权重分配(DWD)算法(ROS)。

Lidar, camera, Radar multi-sensor fusion and Dynamic Weight Distribution (DWD) algorithm (ROS).

This project is able to fusion the targets of lidar, radar and camera, and assign them dynamic weights according to the Kalman filter effect. And make it running in ROS.

Dependence

  • Ubuntu 18.04
  • ROS melodic
  • CUDA 10.0
  • Caffe
  • Opencv
  • PCL

Introduction

This project has a total of four folders, which need to be built separately.

Build the cnn_seg_lidar

install the catkin build tool:

sudo apt-get install python-catkin-tools

build this project:

cd cnn_seg_lidar/
catkin build

Build the darknet_yolov4_ros

cd darknet_yolov4_ros/
catkin_make

Build the kitti_player

cd kitti_player/
catkin_make

Build the sensor_fusion

cd sensor_fusion/
catkin_make

Run this project

open a new terminal

cd kitti_player/
source devel/setup.bash
roslaunch kitti_player kittiplayer_standalone.launch

open a new terminal

cd cnn_seg_lidar/
source devel/setup.bash
roslaunch lidar_cnn_seg_detect lidar_cnn_seg_detect.launch 

open a new terminal

cd darknet_yolov4_ros/
source devel/setup.bash
roslaunch darknet_ros yolo_v4.launch

open a new terminal

cd sensor_fusion/
source devel/setup.bash
rosrun pcl_deal pointdeal

open a new terminal

cd sensor_fusion/
source devel/setup.bash
rosrun opencv_deal showROI 

open a new terminal

cd sensor_fusion/
source devel/setup.bash
rosrun depthGet depthget

Citation

If necessary, please cite references in the following format.

《无人驾驶汽车多传感器冗余下的数据融合算法研究》https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CMFD&dbname=CMFD202201&filename=1021903448.nh&uniplatform=NZKPT&v=t5M0EWN6evoE2ju_W3yHNTCQtrs2a8AV05S9fGArHaoCTqXwolD5fLvAW5rufShL

Citation in GB/T 7714-2015 format

[1]周文起. 无人驾驶汽车多传感器冗余下的数据融合算法研究[D].哈尔滨工业大学,2021.DOI:10.27061/d.cnki.ghgdu.2021.004217.

Citation in Bibtex format

@mastersthesis{周文起 2021 无人驾驶汽车多传感器冗余下的数据融合算法研究 ,
author={周文起},
title={ 无人驾驶汽车多传感器冗余下的数据融合算法研究 },
school={哈尔滨工业大学},
year={2021},
type={硕士论文},
month={},
}

“Multi-target Detection based on Multi-sensor Redundancy and Dynamic Weight Distribution for Driverless Cars” https://ieeexplore.ieee.org/document/9446002

Citation in GB/T 7714-2015 format

[1]Q. Liu, W. Zhou, Y. Zhang and X. Fei, "Multi-target Detection based on Multi-sensor Redundancy and Dynamic Weight Distribution for Driverless Cars," 2021 International Conference on Communications, Information System and Computer Engineering (CISCE), 2021, pp. 229-234, doi: 10.1109/CISCE52179.2021.9446002.

Citation in Bibtex format:

@INPROCEEDINGS{9446002,
  author={Liu, Qinghe and Zhou, Wenqi and Zhang, Yankun and Fei, Xun},
  booktitle={2021 International Conference on Communications, Information System and Computer Engineering (CISCE)}, 
  title={Multi-target Detection based on Multi-sensor Redundancy and Dynamic Weight Distribution for Driverless Cars}, 
  year={2021},
  volume={},
  number={},
  pages={229-234},
  doi={10.1109/CISCE52179.2021.9446002}}

About

Lidar, camera, Radar multi-sensor fusion and Dynamic Weight Distribution (DWD) algorithm (ROS) . This project is able to fusion the targets of lidar, radar and camera, and assign them dynamic weights according to the Kalman filter effect. And make it running in ROS.


Languages

Language:Makefile 45.3%Language:CMake 13.2%Language:Python 10.2%Language:C 9.9%Language:Common Lisp 8.6%Language:C++ 7.9%Language:JavaScript 3.3%Language:Shell 1.1%Language:Cuda 0.5%