6 papers · 1 filter
Extending Ground-Constraint LiDAR-IMU Calibration to Tilted Surfaces in a Continuous-Time Framework
Vassili Korotkine, Pierre Chamoun, Mohammed Ayman Shalaby +1
This paper presents a novel method that extends targetless LiDAR-IMU calibration for ground vehicles to non- flat environments. Calibration typically necessitates full exci- tation…
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…
Globally Optimal Data-Association-Free Landmark-Based Localization Using Semidefinite Relaxations
Vassili Korotkine, Mitchell Cohen, James Richard Forbes
This paper proposes a semidefinite relaxation for landmark-based localization with unknown data associations in planar environments. The proposed method simultaneously solves for t…
A Hessian for Gaussian Mixture Likelihoods in Nonlinear Least Squares
Vassili Korotkine, Mitchell Cohen, James Richard Forbes
This paper proposes a novel Hessian approximation for Maximum a Posteriori estimation problems in robotics involving Gaussian mixture likelihoods. Previous approaches manipulate th…
navlie: A Python Package for State Estimation on Lie Groups
Charles Champagne Cossette, Mitchell Cohen, Vassili Korotkine +3
The ability to rapidly test a variety of algorithms for an arbitrary state estimation task is valuable in the prototyping phase of navigation systems. Lie group theory is now mains…
Koopman Linearization for Data-Driven Batch State Estimation of Control-Affine Systems
Zi Cong Guo, Vassili Korotkine, James R. Forbes +1
We present the Koopman State Estimator (KoopSE), a framework for model-free batch state estimation of control-affine systems that makes no linearization assumptions, requires no pr…