1 citations · 1 across the 7 of their papers we have counts for
7 papers
Smoothing Out the Edges: Continuous-Time Estimation with Gaussian Process Motion Priors on Factor Graphs
Connor Holmes, Sven Lilge, Zi Cong Guo +2
Continuous-time state estimation is gaining in popularity due to its abilities to provide smooth solutions, handle asynchronous sensors, and interpolate between data points. While…
FoMo: A Multi-Season Dataset for Robot Navigation in Forêt Montmorency
Matěj Boxan, Gabriel Jeanson, Alexander Krawciw +5
The Forêt Montmorency (FoMo) dataset is a comprehensive multi-season data collection, recorded over the span of one year in a boreal forest. Featuring a unique combination of on- a…
Sharing the Load: Autonomous Multi-Rover Cargo Transport
Alexander Krawciw, Luka Antonyshyn, Sven Lilge +5
A future lunar habitat, as part of the Artemis program, will require a significant amount of logistics infrastructure. Cargo that is transported to the Moon will need to be moved f…
UAV See, UGV Do: Aerial Imagery and Virtual Teach Enabling Zero-Shot Ground Vehicle Repeat
Desiree Fisker, Alexander Krawciw, Sven Lilge +2
This paper presents Virtual Teach and Repeat (VirT&R): an extension of the Teach and Repeat (T&R) framework that enables GPS-denied, zero-shot autonomous ground vehicle navigation…
Radar Teach and Repeat: Architecture and Initial Field Testing
Xinyuan Qiao, Alexander Krawciw, Sven Lilge +1
Frequency-modulated continuous-wave (FMCW) scanning radar has emerged as an alternative to spinning LiDAR for state estimation on mobile robots. Radar's longer wavelength is less a…
FoMo: A Proposal for a Multi-Season Dataset for Robot Navigation in Forêt Montmorency
Matěj Boxan, Alexander Krawciw, Effie Daum +4
In this paper, we propose the FoMo (Forêt Montmorency) dataset: a comprehensive, multi-season data collection. Located in the Montmorency Forest, Quebec, Canada, our dataset will c…
LaserSAM: Zero-Shot Change Detection Using Visual Segmentation of Spinning LiDAR
Alexander Krawciw, Sven Lilge, Timothy D. Barfoot
This paper presents an approach for applying camera perception techniques to spinning LiDAR data. To improve the robustness of long-term change detection from a 3D LiDAR, range and…