Timothy D. Barfoot

FoMo: A multi-season dataset for robot navigation in Forêt Montmorency

The Forêt Montmorency (FoMo) dataset is a comprehensive multi-season data collection, recorded over the span of 1 year in a boreal forest. Featuring a unique combination of on- and off-pavement environments with significant environmental changes, the dataset challenges establishe...

Smoothing out the edges: continuous-time estimation with Gaussian process motion priors on factor graphs

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 there are two main paradigms, parametric (e.g., temporal basis functions, splines) and nonparametric...