Normalizing Flow-Enhanced Message Passing for Multirobot Collaborative Localization
The algorithm unifies Gaussian belief propagation and mean-field approximation for distributed robot localization. It handles complex nonlinear measurement models by using a normalizing flow-based gradient estimator, allowing for learnable sampling. This approach improves accuracy and robustness in multirobot systems, even surpassing centralized methods.