6 citations · 8 across the 7 of their papers we have counts for
8 papers
Comparing Trajectories from Positions Alone: Curvature-Based Time Alignment and Drift Error Metric
Effie Daum, Daniele De Martini, Claire Dune +1
In field robotics, acquiring independent large-scale reference trajectories more accurate than the evaluated estimates remains an open challenge. The domain is widely reliant on Ab…
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…
ASAP-MO:Advanced Situational Awareness and Perception for Mission-critical Operations
Veronica Vannini, William Dubois, Olivier Gamache +5
Deploying robotic missions can be challenging due to the complexity of controlling robots with multiple degrees of freedom, fusing diverse sensory inputs, and managing communicatio…
UAV-Assisted Self-Supervised Terrain Awareness for Off-Road Navigation
Jean-Michel Fortin, Olivier Gamache, William Fecteau +4
Terrain awareness is an essential milestone to enable truly autonomous off-road navigation. Accurately predicting terrain characteristics allows optimizing a vehicle's path against…
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…
RTS-GT: Robotic Total Stations Ground Truthing dataset
Maxime Vaidis, Mohsen Hassanzadeh Shahraji, Effie Daum +3
Numerous datasets and benchmarks exist to assess and compare Simultaneous Localization and Mapping (SLAM) algorithms. Nevertheless, their precision must follow the rate at which SL…
Benchmarking ground truth trajectories with robotic total stations
Effie Daum, Maxime Vaidis, François Pomerleau
Benchmarks stand as vital cornerstones in elevating SLAM algorithms within mobile robotics. Consequently, ensuring accurate and reproducible ground truth generation is vital for fa…
Uncertainty analysis for accurate ground truth trajectories with robotic total stations
Maxime Vaidis, William Dubois, Effie Daum +2
In the context of robotics, accurate ground truth positioning is essential for the development of Simultaneous Localization and Mapping (SLAM) and control algorithms. Robotic Total…