ebadi/SIMLAN

SIMLAN, Simulation for Indoor Multi-Camera Localization and Navigation

This simulation environment, based on the Gazebo simulator and ROS2, resembles a Volvo trucks' warehouse and serves as a playground for rapid prototyping and testing indoor multi-camera localization, positioning, and navigation algorithms. While this environment can be utilized for Multi-Sensor SLAM (Simultaneous Localization and Mapping) using cameras, IMUs, GPS, lidar, and radar mounted on the robot, the focus of this project is not on mapping but on assuming a fixed building layout and using fixed cameras mounted on the ceiling.

Find technical and more detailed documentation and specifications in the following links:

• Simulation
• Building Gazebo models (Blender/Phobos)
• Objects specifications
• Warehouse specification
• Camera extrinsic calibration and Camera intrinsic calibration

video demo 1 , video demo 2

Click on image below to see the Volvo layout demo:

Installation in development environment

Dependencies: vscode (with Dev containers extension installed) and docker. Make sure to accept installation of vscode extensions when you open the project.

If you have any issue with docker incompatibility, make sure that docker compose or docker-compose is set correctly in the setting.

Additionally you are requested to rebuild in the container that you should also accept. This make take couple of minutes. Run these commands in the vscode terminal after vscode is connected to the docker as shown in image below:

(if you don't see this try to build manually in vscode by pressing Ctrl + Shift + P and select Dev containers: Rebuild and Reopen in container. ) To kill all relevant process (related to gazebo, ros2), delete build files, delete recorded images and rosbag files using the following command:

./start.sh clean

To clean up and build the ros2 simulation

./start.sh build

To kill previously running simulation instances, build the project and start the simulation environment and agents(spawn robots, Aruco marks and cameras on the scene) run the following command and you should be able to see the Gazebo graphical simulation window:

./start.sh sim

Attention: run these commands in a parallel terminal within vscode .

the jackal can then be controlled with the computer keyboard by running:

./start.sh teleop_jackal

To control the infobot using keyboard:

./start.sh teleop_infobot

To record camera images for available cameras we use a simple python code ./processing/camera_subscriber.py that can be executed with following command:

To record continuously:

./start.sh cam_record 164

To record one screenshot:

./start.sh screenshot 164

The result will be stored in ./processing/camera_data/.

Advanced features (not fully supported yet):

To record ros messages in ROS bag files to replay the scenario later:

./start.sh ros_record

To replay the last rosbag recording:

./start.sh ros_replay

(optionally) To do cartography:

./start.sh slam

To start nav2 navigation stack and start commanding the infobot to move in the map:

./start.sh nav

and then:

./start.sh commander

To test the unit tests before pushing new codes:

./start.sh test

Additional information

Please see LICENSE, CREDITS.md and CHANGELOG.md for more information.

This work was carried out within these projects:

• the SMILE IV project financed by Vinnova, FFI, Fordonsstrategisk forskning och innovation under the grant number 2023-00789.
• the EUREKA ITEA4 ArtWork - The smart and connected worker financed by Vinnova under the grant number 2023-00970.