activity
20212026
most citedGraph Laplacian Diffusion Localization of Connected and Automated Vehicles

28 citations · 29 across the 14 of their papers we have counts for

collaborators

14 papers

cs.RO2026

CDKF-Track: Cluster-aware Data-Driven Kalman Filtering for Cooperative 3D Multi-Object Tracking

Maria Damanaki, Nikos Piperigkos, Alexandros Gkillas +1

Multi-Object Tracking (MOT) is essential for EdgeAI perception systems, where accurate object localization and reliable identification enable safe decision-making. Singleagent MOT…

cs.RO2026

Fast and Accurate Outlier-Aware LiDAR Super-Resolution for SLAM Applications

Christos Anagnostopoulos, Alexandros Gkillas, Nikos Piperigkos +1

This work tackles the challenge of enhancing low-resolution LiDAR sensors for SLAM applications through a novel Deep Unrolling-based Super-Resolution (SR) model. We integrate an ou…

cs.CV2025

Guided Model-based LiDAR Super-Resolution for Resource-Efficient Automotive scene Segmentation

Alexandros Gkillas, Nikos Piperigkos, Aris S. Lalos

High-resolution LiDAR data plays a critical role in 3D semantic segmentation for autonomous driving, but the high cost of advanced sensors limits large-scale deployment. In contras…

cs.CR2025

Integrated Simulation Framework for Adversarial Attacks on Autonomous Vehicles

Christos Anagnostopoulos, Ioulia Kapsali, Alexandros Gkillas +2

Autonomous vehicles (AVs) rely on complex perception and communication systems, making them vulnerable to adversarial attacks that can compromise safety. While simulation offers a…

cs.CV2025

Efficient Model-Based Purification Against Adversarial Attacks for LiDAR Segmentation

Alexandros Gkillas, Ioulia Kapsali, Nikos Piperigkos +1

LiDAR-based segmentation is essential for reliable perception in autonomous vehicles, yet modern segmentation networks are highly susceptible to adversarial attacks that can compro…

cs.RO2025★ 1 cited

A holistic perception system of internal and external monitoring for ground autonomous vehicles: AutoTRUST paradigm

Alexandros Gkillas, Christos Anagnostopoulos, Nikos Piperigkos +16

This paper introduces a holistic perception system for internal and external monitoring of autonomous vehicles, with the aim of demonstrating a novel AI-leveraged self-adaptive fra…

cs.CV2025

Robustifying 3D Perception via Least-Squares Graphs for Multi-Agent Object Tracking

Maria Damanaki, Ioulia Kapsali, Nikos Piperigkos +2

The critical perception capabilities of EdgeAI systems, such as autonomous vehicles, are required to be resilient against adversarial threats, by enabling accurate identification a…

cs.CV2025

Optimizing Cooperative Multi-Object Tracking using Graph Signal Processing

Maria Damanaki, Nikos Piperigkos, Alexandros Gkillas +1

Multi-Object Tracking (MOT) plays a crucial role in autonomous driving systems, as it lays the foundations for advanced perception and precise path planning modules. Nonetheless, s…

cs.CV2024

Personalized Federated Learning for Cross-view Geo-localization

Christos Anagnostopoulos, Alexandros Gkillas, Nikos Piperigkos +1

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 het…

cs.RO2024

Federated Data-Driven Kalman Filtering for State Estimation

Nikos Piperigkos, Alexandros Gkillas, Christos Anagnostopoulos +1

This paper proposes a novel localization framework based on collaborative training or federated learning paradigm, for highly accurate localization of autonomous vehicles. More spe…

eess.IV2023

Real time enhancement of operator's ergonomics in physical human-robot collaboration scenarios using a multi-stereo camera system

Gerasimos Arvanitis, Nikos Piperigkos, Christos Anagnostopoulos +2

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 add…

eess.SP2021★ 28 cited

Graph Laplacian Diffusion Localization of Connected and Automated Vehicles

Nikos Piperigkos, Aris S. Lalos, Kostas Berberidis

In this paper, we design distributed multi-modal localization approaches for Connected and Automated vehicles. We utilize information diffusion on graphs formed by moving vehicles,…

eess.SP2021

Cooperative Multi-Modal Localization in Connected and Autonomous Vehicles

Nikos Piperigkos, Aris S. Lalos, Kostas Berberidis +1

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 expecte…

eess.SY2021

Empowering cyberphysical systems of systems with intelligence

Stavros Nousias, Nikos Piperigkos, Gerasimos Arvanitis +3

Cyber Physical Systems have been going into a transition phase from individual systems to a collecttives of systems that collaborate in order to achieve a highly complex cause, rea…