MSS

Clone this repository — Quick (recommended)

# HTTPS (recommended)
git clone --recurse-submodules --shallow-submodules --jobs 4 \
	https://gitlab.tu-clausthal.de/geomatics-teaching/mss_lecture.git
cd mss_lecture

# SSH (if you use SSH keys)
git clone --recurse-submodules --shallow-submodules --jobs 4 \
	git@gitlab.tu-clausthal.de:geomatics-teaching/mss_lecture.git
cd mss_lecture

# If you already cloned without submodules
git submodule update --init --recursive

Multi-Sensor Floating System (ROS1 + ROS2 Hybrid Architecture)

Overview

This project provides a ROS 2 focused multi-sensor system targeting Jetson platforms (JetPack 5.1.2, Ubuntu 20.04).

Supported and maintained:

• ROS 2 (foxy / humble)
• Hesai LiDAR (ROS 2)
• SBG IMU (ROS 2)
• Camera driver (ROS 2)
• Arduino thruster (ROS 2)
• SLAM (not test ros2 yet)

Note: ROS 1 (Noetic) support is deprecated and no longer actively maintained in this repository.

Quick start

• Work from the repository root (~/EAGRUMO) so helper scripts resolve relative paths correctly.
• Helper scripts live under ./scripts/ros1/ (ROS1 wrappers) and ./scripts/ros2/ (ROS2 wrappers). Use these to launch bringups quickly:
  • ROS1 example: ./scripts/ros1/run_lidar.sh
  • ROS2 example (all sensors with recording): ./scripts/ros2/run_ros2_all_record.sh

Rosbag output defaults

• Default behavior: When recording is enabled via the ROS2 helpers or --record-bag, the default bag output is created under the repository temp/ directory with a timestamped name, e.g. temp/rosbag2_20251128_173045.
• Override: You can override the output name with --bag-output NAME (script) or bag_output:=NAME (launch argument), or change topics/output via config/rosbag/rosbag_ros2.yaml.

How to verify a recording

• Start a bringup with recording:

./scripts/ros2/run_ros2_all_record.sh
# or
./scripts/ros2/run_ros2_all.sh --record-bag

• Check for created bag folders:

ls -lh temp/rosbag2_*
# Inspect a bag's metadata
ros2 bag info temp/rosbag2_<TIMESTAMP>

Notes

• Recording is off by default; enable it with the wrappers above. The launch uses the ros2 bag CLI to start recording (robust against differing package layouts).
• If a bag does not appear, capture the launch log output and check that ros2 bag record started successfully; errors may indicate missing topics or environment setup issues.

SLAM status

• ROS2 SLAM support in this repository is not yet ready. See the project TODO for next steps (evaluation of Fast-LIVO2 / MOLA, dependency list, and example launches).

Gazebo Simulation

VRX (Virtual RobotX) simulation environment for testing WAM-V systems with ROS 2 Jazzy + Gazebo Harmonic.

Quick start:

cd gazebo
colcon build --merge-install
source install/setup.bash

Features:

• WAM-V generation from YAML (components, sensors, thrusters)
• Marine environment (waves, buoyancy, multiple world scenarios)
• RGL LiDAR plugin, auto-recording, gamepad teleop

See also: gazebo/README.md for detailed usage.

Development Guidelines

Branch workflow:

• Always create a new branch for development work — do not commit directly to main
• Use descriptive branch names (e.g., feature/new-sensor, fix/imu-calibration)

Working with submodules:

This repository uses git submodules for package management. When developing code inside a submodule:

1. Navigate to the submodule directory (e.g., ros2_ws/src/camera/)
2. Create and checkout a development branch in the submodule repository:

   cd ros2_ws/src/camera
   git checkout -b feature/my-camera-update

3. Make your changes and commit within the submodule
4. Push the submodule branch to its remote repository
5. Return to the main repository root and commit the submodule reference update:

   cd /path/to/mss_lecture
   git add ros2_ws/src/camera
   git commit -m "Update camera submodule to feature branch"

Important: Each submodule is an independent git repository. Branch changes must be made in both the submodule repository and tracked in the parent repository.

AI-assisted development:

• Use AI tools (GitHub Copilot, ChatGPT, Claude, etc.) to accelerate development
• Ask AI for code reviews, debugging help, and implementation suggestions
• Leverage AI for documentation, test generation, and refactoring tasks