Tracked targets often exhibit common behaviors due to influences from the surrounding
environment, such as wind or obstacles, which are usually modeled as noise. Here, these …

We present a deliberative trajectory planning method to avoid collisions with traffic vessels. It
also plans traversal across wavefields generated by these vessels and minimizes the risk of …

We present a method to model and classify trajectory data that come from surveillance
videos. Observations of the locations of moving entities are used to estimate their expected …

Learning to recognize common activities such as traffic activities and robot behavior is an
important and challenging problem related both to AI and robotics. We propose an …

Lattice-based motion planning is a hybrid planning method where a plan is made up of
discrete actions, while simultaneously also being a physically feasible trajectory. The …

4.1 The availability of devices with location tracking capability has helped generate a
tremendous amount of trajectory data of humans, animals, vehicles, and drones, which is …

Spatio-temporal data is a commonly used source of information. Using machine learning to
analyse this kind of data can lead to many interesting and useful insights. In this thesis …

The Gaussian process regression (GPR) has been applied to model trajectory points from
Global Navigation Satellite System (GNSS). Trajectory modeling using GP in previous works …

The Global Navigation Satellite Systems (GNSS) have been used in autonomous vehicles
and remote sensing. The GNSS receiver can be a conventional device or an enhanced …

Advances in sensing and computing hardware have physically equipped robots to operate
in complex environments. In many real-world settings, we desire robots to operate at a high …