23 citations · 41 across the 9 of their papers we have counts for
12 papers · 1 filter
Online Stochastic Variational Gaussian Process Mapping for Large-Scale SLAM in Real Time
Ignacio Torroba, Marco Chella, Aldo Teran +2
Autonomous underwater vehicles (AUVs) are becoming standard tools for underwater exploration and seabed mapping in both scientific and industrial applications \cite{graham2022rapid…
Data-driven Loop Closure Detection in Bathymetric Point Clouds for Underwater SLAM
Jiarui Tan, Ignacio Torroba, Yiping Xie +1
Simultaneous localization and mapping (SLAM) frameworks for autonomous navigation rely on robust data association to identify loop closures for back-end trajectory optimization. In…
Fully-probabilistic Terrain Modelling with Stochastic Variational Gaussian Process Maps
Ignacio Torroba, Christopher Illife Sprague, John Folkesson
Gaussian processes (GPs) are becoming a standard tool to build terrain representations thanks to their capacity to model map uncertainty. This effectively yields a reliability meas…
Interpretability in Contact-Rich Manipulation via Kinodynamic Images
Ioanna Mitsioni, Joonatan Mänttäri, Yiannis Karayiannidis +2
Deep Neural Networks (NNs) have been widely utilized in contact-rich manipulation tasks to model the complicated contact dynamics. However, NN-based models are often difficult to d…
Towards Autonomous Industrial-Scale Bathymetric Surveying
Ignacio Torrobam Nils Bore, John Folkesson
Both higher efficiency and cost reduction can be gained from automating bathymetric surveying for offshore applications such as pipeline, telecommunication or power cables installa…
PointNetKL: Deep Inference for GICP Covariance Estimation in Bathymetric SLAM
Ignacio Torroba, Christopher Iliffe Sprague, Nils Bore +1
Registration methods for point clouds have become a key component of many SLAM systems on autonomous vehicles. However, an accurate estimate of the uncertainty of such registration…