5 accepted papers
Autonomous inspection tasks require path-planning algorithms to efficiently gather observations from points of interest (POIs). However, localization errors in urban environments introduce execution uncertainty, posing challenges to successfully completing such tasks. Existing inspection-planning al…
Surface grading, the process of leveling an uneven area containing pre-dumped sand piles, is an important task in the construction site pipeline. This labour-intensive process is often carried out by a bulldozer, a key machinery tool at any construction site. Current attempts to automate surface gra
The Kalman filter (KF) is a widely-used algorithm for tracking the latent state of a dynamical system from noisy observations. For systems that are well-described by linear Gaussian state space models, the KF minimizes the mean-squared error (MSE). However, in practice, observations are corrupted by…
Depth estimation is critical for any robotic system. In the past years, the estimation of depth from monocular images has shown great improvement. However, in the underwater environment results are still lagging behind due to appearance changes caused by the medium. So far little effort has been inv…
Providing a metric of uncertainty alongside a state estimate is often crucial when tracking a dynamical system. Classic state estimators, such as the Kalman filter (KF), provide a time-dependent uncertainty measure from knowledge of the underlying statistics; however, deep learning based tracking sy…