Dynamic-VINS is a real-time RGB-D Inertial Odometry system for resource-restricted robots in dynamic environments.
- Dynamic feature recognition by object detection and depth information with the performance comparable to semantic segmentation.
- Grid-based feature detection and efficient high-quality FAST feature extraction.
- Competitive localization accuracy and robustness in dynamic environments are shown in a real-time application on resource-restricted platforms, such as HUAWEI Atlas200 DK, NVIDIA Jetson AGX Xavier.
Authors: Jianheng Liu, Xuanfu Li, Yueqian Liu, and Haoyao Chen from the Networked RObotics and Sytems Lab, HITSZ
If you use Dynamic-VINS for your academic research, please cite the following paper [pdf].
@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}}
Video links: Youtube or Bilibili.
Tested on Ubuntu 18.04 and 20.04.
Find how to install Dynamic-VINS and its dependencies here: Installation instructions.
Download OpenLORIS datasets.
Take OpenLORIS-cafe as examples.
tar -xzvf cafe1-1_2-rosbag.tar
cd cafe
rosbag decompress cafe*
python YOUR_PATH_TO_DYNAMIC_VINS/scripts/merge_imu_topics.py cafe1-1.bag cafe1-2.bag
NVIDIA devices (pytorch)
roslaunch vins_estimator openloris_vio_pytorch.launch
roslaunch vins_estimator vins_rviz.launch # Visualization
rosbag play YOUR_PATH_TO_DATASET/cafe.bag
NVIDIA devices (tensorrt)
roslaunch vins_estimator openloris_vio_tensorrt.launch
roslaunch vins_estimator vins_rviz.launch # Visualization
rosbag play YOUR_PATH_TO_DATASET/cafe.bag
HUAWEI Atlas200DK
roslaunch vins_estimator openloris_vio_atlas.launch
Running Dynamic-VINS on HUAWEI Atlas200DK requires multile devices communication setting. For specific instructions, please refer to the MULTIPLE_DEVICES. And other kinds of edge devices also could refer to this instruction.
Please prepare enough space for the datasets.
- HITSZ(41.0GB x 2)
- THUSZ(51.3GB x 2)
- download datasets vis Dyanmic-VINS-Datasets.
- run following cmd:
# bash scripts/download_hitsz.sh # bash scripts/download_thusz.sh
python3 scipts/rosbag_merge_chunk.py Datasets/hitsz_00.bag # python3 scipts/rosbag_merge_chunk.py Datasets/hitsz_00.bag
# rm ./Datasets/hitsz_*.bag # rm ./Datasets/thusz_*.bag
roslaunch vins_estimator realsense_vio_campus.launch
roslaunch vins_estimator vins_rviz.launch
rosbag play Datasets/hitsz.bag # rosbag play thusz.bag
- Detailed illustration of configuration please refer to realsense configuration.
- A running procedure across two different platform is exampled in Multiple Devices running_procedure.
- HUAWEI Atlas200DK setup please refer to HUAWEI Atlas200DK Setup.
Dynamic-VINS is extended based on VINS-Mono, VINS-RGBD, yolov5, tensorrt_yolov5, ascend_yolo.