A major challenge of today's production systems in the context of Industry 4.0 and Cyber-
Physical Production Systems is to be flexible and adaptive whilst being robust and …

This paper introduces Probabilistic Chekov (p-Chekov), a chance-constrained motion
planning system that can be applied to high degree-of-freedom (DOF) robots under motion …

This article investigates stochastic invariance for control systems through probabilistic
controlled invariant sets (PCISs). As a natural complement to robust controlled invariant sets …

An efficient and safe evacuation of passengers is important during emergencies.
Overcapacity on a route can cause an increased evacuation time. Decision making is …

Many path planning algorithms developed for land or air based autonomous vehicles no
longer apply under the water. A time-optimal path planning method for autonomous …

A framework capable of computing optimal control policies for a continuous system in the
presence of both action and environment uncertainty is presented in this work. The …

Construction processes can be implemented in most cases using various sorts of
equipment. These can move along various paths, over the construction site from one job to …

This work presents a framework for fast reconfiguration of local control policies for a
stochastic system to satisfy a high-level task specification. The motion of the system is …

Motion planning is a core problem in many applications spanning from robotic manipulation
to autonomous driving. Given its importance, several schools of methods have been …

In this paper, we propose an accurate automatic defect detection method using the quadtree
decomposition on scanning electron microscope (SEM) images. The proposed method …