Accurate localization and mapping in a large-scale environment is an essential system of an
autonomous vehicle. The difficulty of the previous LiDAR or LiDAR-inertial simultaneous …

To solve the problems that the basic ant colony algorithm (ACO) is easy to fall into the local
optimum, the path is too long and there are too many turns when searching the path of the …

Operating unmanned aerial vehicles (UAVs) in complex environments that feature dynamic
obstacles and external disturbances poses significant challenges, primarily due to the …

We present an approach for safe motion planning under robot state and environment
(obstacle and landmark location) uncertainties. To this end, we first develop an approach …

Online generation of collision free trajectories is of prime importance for autonomous
navigation. Dynamic environments, robot motion and sensing uncertainties adds further …

Recent research has enabled fixed-wing unmanned aerial vehicles (UAVs) to maneuver in
constrained spaces through the use of direct nonlinear model predictive control (NMPC)[1] …

Mobile robots are undergoing tremendous development, which makes them employed in
many fields. In this area, global localization in symmetric indoor environments is a commonly …

Computing collision-free trajectories is of prime importance for safe navigation. We present
an approach for computing the collision probability under Gaussian distributed motion and …

Mobile robots are undergoing tremendous development, which makes them employed in
many fields. In this area, global localization in symmetric indoor environments is a commonly …

In this thesis we investigate the problem of motion planning under environment uncertainty.
Specifically, we focus on Task-Motion Planning (TMP) and probabilistic collision avoidance …