activity
20242026
collaborators

9 papers

cs.RO2026

ARC: Adaptive Robust Joint State and Covariance Estimation

Alexandre Hadji-Thomas, Andrew Stirling, James R. Forbes

Sensor measurements are frequently corrupted by outliers and non-Gaussian noise. These imperfections in the sensor data can cause classical state estimators to generate biased and…

cs.RO2026

Observability and Consistency Analysis for Visual-Inertial Navigation with Anchored Feature Parameterizations

Mitchell Cohen, Vassili Korotkine, James Richard Forbes

This paper presents an analysis of the observability and consistency properties of filtering-based visual-inertial navigation systems (VINS) that utilize anchored feature represent…

cs.RO2026

KILO-EKF: Koopman-Inspired Learned Observations Extended Kalman Filter

Zi Cong Guo, James R. Forbes, Timothy D. Barfoot

We present the Koopman-Inspired Learned Observations Extended Kalman Filter (KILO-EKF), which combines a standard EKF prediction step with a correction step based on a Koopman-insp…

cs.RO2026

Gaussian Variational Inference with Non-Gaussian Factors for State Estimation: A UWB Localization Case Study

Andrew Stirling, Mykola Lukashchuk, Dmitry Bagaev +2

This letter extends the exactly sparse Gaussian variational inference (ESGVI) algorithm for state estimation in two complementary directions. First, ESGVI is generalized to operate…

eess.SY2026

Nonlinear Observer Design for Visual-Inertial Odometry

Mouaad Boughellaba, Abdelhamid Tayebi, James R. Forbes +1

This paper addresses the problem of Visual-Inertial Odometry (VIO) for rigid body systems evolving in three-dimensional space. We introduce a novel matrix Lie group structure, deno…

eess.SY2025

dkpy: Robust Control with Structured Uncertainty in Python

Timothy Everett Adams, Steven Dahdah, James Richard Forbes

Models used for control design are, to some degree, uncertain. Model uncertainty must be accounted for to ensure the robustness of the closed-loop system. -analysis and -sy…