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[Software] Releasing the Modular and Efficient Multi-Sensor Fusion Framework MaRS

MaRS: Truly modular multi-sensor fusion framework now available

If you are interested in modular sensor-fusion with minimal State-Representation despite a high number of sensors and their calibration states, then you might also be interested in our first release of the MaRS Framework.

We are happy to announce that our in-house developed state-estimation framework “MaRS” is now available on github. You can add any number of sensors to a setup and use their information efficiently. The core software is provided as a stand-alone C++ library, ready for the integration in any middle-ware tool. We also provide a ROS wrapper for this library with example setups to get your project off the ground quickly.

Feel free to visit the MaRS GitHub pages.

Some of the Highlights
MaRS Framework (Stand-Alone C++ Library)

  • Truly modular decoupling of sensor-states from the core navigation-states
  • Generalized covariance segmentation for plug and play state and covariance blocks
  • Minimal state-representation at any point in time
  • Integration and removal of sensor modules during runtime
  • Out of sequence sensor measurement handling
  • Developed for computationally constrained platforms
  • Efficient handling of asynchronous and multi-rate sensor information
  • Separation between simple user interaction and the complexity of information handling
  • Google tests and Docker test environment

ROS Wrapper

  • Ready to use ROS nodes for common setups (position, pose, and GNSS sensors with IMU)
  • Predefined sensor update modules (plug and play)
  • Predefined RQT views
  • Docker test environment

More Information
The RA-L paper: MaRS: A Modular and Robust Sensor-Fusion Framework | IEEE Journals & Magazine | IEEE Xplore

Method animation:

Real-world demo video:

Looking forward to your feedback and videos of your MaRS powered autonomous robots,
Christian Brommer, Roland Jung, Jan Steinbrener and Stephan Weiss

8 Likes

Very cool project!

I saw you used PX4 for the real-world demo. Can you provide some more detail on how this worked? Did you use the RTPS bridge and run MaRS on the onboard computer or did you make it run directly on the flight controller? How does the latency compare with PX4’s EKF2?