For autonomous robots to navigate a complex environment, it is crucial to understand the
surrounding scene both geometrically and semantically. Modern autonomous robots employ …

In the evolving landscape of manufacturing, the integration of intelligent control theory
stands as a pivotal advancement, driving both process optimization and the paradigm of …

This paper presents a novel approach for tracking static and dynamic objects for an
autonomous vehicle operating in complex urban environments. Whereas traditional …

The task of object detection and tracking is one of the most complex and challenging
problems in artificial intelligence (AI) systems that model perception. Object tracking has …

In this paper, we present a novel artificial intelligence-based fog controller, called FogAI that
provides a versatile control mechanism to the fog layer. FogAI not only abstracts the control …

Object tracking is the task of estimating over time the state of a single or multiple objects
based on noisy measurements received from one or several sensors. The field of object …

Reliably predicting future occupancy of highly dynamic urban environments is an important
precursor for safe autonomous navigation. Common challenges in the prediction include …

In this paper, a plain data-driven and simulation-based approach to object tracking is
investigated. The basic idea is to use the probabilistic model of the tracking problem to …

The recent emergence of object proposal algorithms in the computer vision community
shows great promise to addressing difficult problems in robotic such as object discovery and …

An environment representation (ER) is a substantial part of every autonomous system. It
introduces a common interface between perception and other system components, such as …