2 citations · 2 across the 3 of their papers we have counts for
3 papers · 1 filter
iMESA: Incremental Distributed Optimization for Collaborative Simultaneous Localization and Mapping
Daniel McGann, Michael Kaess
This paper introduces a novel incremental distributed back-end algorithm for Collaborative Simultaneous Localization and Mapping (C-SLAM). For real-world deployments, robotic teams…
Learning Covariances for Estimation with Constrained Bilevel Optimization
Mohamad Qadri, Zachary Manchester, Michael Kaess
We consider the problem of learning error covariance matrices for robotic state estimation. The convergence of a state estimator to the correct belief over the robot state is depen…
Group- consistent measurement set maximization via maximum clique over k-Uniform hypergraphs for robust multi-robot map merging
Brendon Forsgren, Ram Vasudevan, Michael Kaess +2
This paper unifies the theory of consistent-set maximization for robust outlier detection in a simultaneous localization and mapping framework. We first describe the notion of pair…