C. Anagnostopoulos

• Dipl.-Ing Electrical and Computer Engineering MSc
• Athena Research and Innovation Center In Information Communication & Knowledge Technologies

The unprecedented technological advancements in Artificial Intelligence (AI) and the Internet of Things (IoT) have given rise to ecosystems of intelligent, interconnected devices, forming the Artificial Intelligence of Things (AIoT). These systems, due to security and privacy concerns, necessitate solutions that adhere to the data-driven learning p...

In this paper we propose a methodology combining Federated Learning (FL) with Cross-view Image Geo-localization (CVGL) techniques. We address the challenges of data privacy and heterogeneity in autonomous vehicle environments by proposing a personalized Federated Learning scenario that allows selective sharing of model parameters. Our method implem...

This paper proposes a novel localization framework based on collaborative training or federated learning paradigm, for highly accurate localization of autonomous vehicles. More specifically, we build on the standard approach of KalmanNet, a recurrent neural network aiming to estimate the underlying system uncertainty of traditional Extended Kalman...

Simultaneous localization and mapping (SLAM) for positioning of robots and autonomous systems and mapping of their surrounding environments is a task of major significance in various applications. However, the main disadvantage of traditional SLAM is that the deployed backend modules suffer from accumulative error caused by sharp viewpoint changes,...

Virtual and augmented reality are currently enjoying a great deal of attention from the research community and the industry towards their adoption within industrial spaces and processes. However, the current design and implementation landscape is still very fluid, while the community as a whole has not yet consolidated into concrete design directio...

In this paper we investigate the impact of federated learning on deep learning-based feature extraction used for self-localization in autonomous vehicles. The accurate and reliable determination of the vehicle's position is crucial for both safety and efficiency purposes. Deep-learning based feature extractors have demonstrated benefits over model-...

In collaborative tasks where humans work alongside machines, the robot's movements and behaviour can have a significant impact on the operator's safety, health, and comfort. To address this issue, we present a multi-stereo camera system that continuously monitors the operator's posture while they work with the robot. This system uses a novel distri...

Empowering each vehicle with four dimensional (4D) situational awareness, i.e., accurate knowledge of neighboring vehicles' 3D locations over time in a cooperative manner (instead of focusing only on self-localization), is fundamental for improving autonomous driving performance in diverse traffic conditions. For this task, identification, localiza...

We are currently witnessing an increased occurrence of extreme weather events, causing a great deal of disruption and distress across the globe. In this setting, the importance and utility of Early Warning Systems is becoming increasingly obvious. In this work, we present the design of an early warning system called TransCPEarlyWarning, aimed at se...

Digital twins are quickly becoming a popular tool in several domains, taking advantage of recent advancements in the Internet of Things, Machine Learning and Big Data, while being used by both the industry sector and the research community. In this paper, we review the current research landscape as regards digital twins in the field of smart cities...

Cooperative Localization is expected to play a crucial role in various applications in the field of Connected and Autonomous vehicles (CAVs). Future 5G wireless systems are expected to enable cost-effective Vehicle-to-Everything (V2X)systems, allowing CAVs to share with the other entities of the network the data they collect and measure. Typical me...

Industrial automation and control environments has indicative examples of complex distributed systems where the IoT deployment pattern of edge measurements and cloud-based analytics does not always fit all requirements. Intelligent embedded devices executing critical functionality and communicating, in real-time or not, through well-structured netw...

The manufacturing environment is characterized by increased complexity with different devices, systems and applications that need to interoperate, while residing at different layers of the classical industrial environment hierarchy. The introduction of the Industrial Internet of Things with increasingly smarter devices drives towards flatter hierar...

Current trends in the manufacturing environment drive towards decentralized distributed systems and the dissolution of traditional rigid hierarchical schemes. Multi Agent Systems (MAS) can be utilized to this end increasing the autonomy and flexibility in the industrial environment. The Internet of Things (IoT) maps also well with these trends offe...

Simulation is a tool offering several advantages in the field of automated manufacturing systems, permitting their analysis and evaluation overcoming complexity, cost, scaling, risk, and timing issues. Gamification technologies may complement limitations of conventional engineering systems towards a more natural human way of working. A gaming platf...

The present paper presents a methodology guide for the transformation of research results into innovations. This methodology guide provides a detailed break-down of the process for the transformation of research to innovation into its distinct steps and identifies the different skills that are needed for the implementation of each step. The steps o...

Innovation represents a challenge for research teams, SMEs, large industries and economies in general, as it is viewed as a catalyst for competitiveness in an increasingly competitive world. Reaching significant research results and achieving technological progress does not by each own create a competitive advantage. A further step is needed in ord...