Miguel A. Saavedra-Ruiz — accepted AI-conference papers

2025

Perpetua: Multi-Hypothesis Persistence Modeling for Semi-Static Environments

Miguel A. Saavedra-Ruiz, Samer B. Nashed, Charlie Gauthier, Liam Paull

IROS 2025

Many robotic systems require extended deployments in complex, dynamic environments. In such deployments, parts of the environment may change between subsequent robot observations. Most robotic mapping or environment modeling algorithms are incapable of representing dynamic features in a way that ena

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2025

The Harmonic Exponential Filter for Nonparametric Estimation on Motion Groups

Miguel A. Saavedra-Ruiz, Steven A. Parkison, Ria Arora, James Richard Forbes, Liam Paull

RA-L 2025

Bayesian estimation is a vital tool in robotics as it allows systems to update the robot state belief using incomplete information from noisy sensors. To render the state estimation problem tractable, many systems assume that the motion and measurement noise, as well as the state distribution, are a

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