MaRS: A Modular and Robust Sensor-Fusion Framework

This research paper presents a modular sensor-fusion framework that allows for the addition and removal of sensors during runtime in dynamic environments. The framework handles system and sensor initialization, measurement updates, and switching of asynchronous multi-rate sensor information with sensor self-calibration. It also has the ability to handle delayed measurements, out-of-sequence updates, and monitor sensor health. The introduced true-modularity is based on covariance segmentation, allowing the processing of propagation and updates on a per-sensor basis. The framework was tested in a precision landing scenario using GNSS, barometer, and vision measurements in both simulation and real-world scenarios. The framework is open-sourced and available for the community to use.