Distributed Simultaneous Localisation and Auto-Calibration using Gaussian Belief Propagation

We present a novel scalable, fully distributed, and online method for simultaneous localisation and extrinsic calibration for multi-robot setups. Individual a priori unknown robot poses are probabilistically inferred as robots sense each other while simultaneously calibrating their sensors and markers extrinsic using Gaussian Belief Propagation. In the presented experiments, we show how our method not only yields accurate robot localisation and auto-calibration but also is able to perform under challenging circumstances such as highly noisy measurements, significant communication failures or limited communication range.

Summary Video

@article{Murai:etal:RAL2024,
    title={Distributed Simultaneous Localisation and Auto-Calibration Using Gaussian Belief Propagation},
    author={Murai, Riku and Alzugaray, Ignacio and Kelly, Paul HJ and Davison, Andrew J},
    journal={IEEE Robotics and Automation Letters},
    year={2024},
    publisher={IEEE}
}      

The authors would like to thank Eric Dexheimer for insightful discussions.