BlueRov SLAM

Welcome! This repo contains the code for BlueROV sonar-based SLAM. This system uses a source of dead-reckoning, in our case a DVL and IMU with environment observations from an imaging sonar to perform graph-based pose slam using the ISAM2 backend implemented by gtsam. This method employs the scan matching paradigm to align scans using dead-reckoning as an initial guess. Point clouds for ICP are generated by converting sonar images to in-plane clouds. Note that this system is 3DOF and we assume fixed depth motion.

This is the original work of Jinkun Wang. The documentation, maintenance, and active development are by John McConnell.

Sensor overview

Our vehicle is documented in this repo https://github.com/jake3991/Argonaut.git. The highlights are the following pieces of hardware.

Occulus M750d imaging sonar
Occulus M1200 imaging sonar (optional)
Rowe SeaPilot DVL
Vectornav 100 MEMS IMU
Bar30 pressure sensor
KVH-DSP-1760 fiber optic gyroscope (optional)

Python Dependencies, note python-3

cv_bridge
gtsam
matplotlib
message_filters
numpy
opencv_python
rosbag
rospy
scikit_learn
scipy
sensor_msgs
Shapely
tf
tqdm
pyyaml

ROS Dependencies

ROS-noetic
catkin-pybind11
catkin-tools

Installation

Ensure all python dependencies are installed
Check ros distro
clone this repo into your catkin workspace
clone git clone https://github.com/ethz-asl/libnabo.git into your catkin workspace
clone https://github.com/ethz-asl/libpointmatcher.git into your catkin workspace
clone https://github.com/jake3991/Argonaut.git into your catkin workspace
build your workspace with catkin build NOT catkin_make

Sample data

We provide a rosbag data file to test and run the SLAM system. Available here: https://drive.google.com/file/d/1nmiFfyk8mVssLqgac7BOe4_RPBP6Wnc9/view?usp=sharing

Running "Online"

This will launch the SLAM system, then we will playback the data as if it is happening now.

source catkin_ws/devel/setup.bash
roslaunch bruce_slam slam.launch
rosbag play your_data.bag

Running Offline

This runs our offline mode, great for quick testing/tuning of parameters.

source catkin_ws/devel/setup.bash
roslaunch bruce_slam slam.launch file:=path_to_data/your_data.bag

Configuration

This SLAM system has many parameters, please read the wiki for an explanation of each parameter. However, we highly recommend using the default parameters in the config folder. If you are to tune anything it would be the feature extraction node in feature.yaml.

Current To Do list

enhance some of the cpp documentation for CFAR

Citation

If you use this repo please cite the following work. Link to pre-print here: https://arxiv.org/abs/2202.08359

@inproceedings{
  title={Virtual Maps for Autonomous Exploration of Cluttered Underwater Environments},
  author={Jinkun Wang, Fanfei Chen, Yewei Huang, John McConnell, Tixiao Shan, and Brendan Englot},
  booktitle={IEEE Journal of Oceanic Engineering,
  year={2022},
  organization={IEEE}
}

SatoshiRobatoFujimoto / sonar-SLAM