Robotics & Cognitive Systems (RCS) unit is a multidisciplinary research group committed to developing intelligent technologies that seamlessly integrate robotics, artificial intelligence (AI), and distributed ledger technologies (DLT). Our mission is to create robust, adaptive, and human-centered systems that address real-world challenges across various domains. We work across several key areas.
- In robotics, we develop autonomous robotic systems that can move, sense, and make decisions on their own.
- In artificial intelligence (AI), we design models for healthcare, distributed manufacturing, and social services—where we leverage Large Language Models (LLMs) as the reasoning engine to build advanced AI chatbots.
- In DLT, we build tools like digital wallets, secure supply chain platforms, and decentralized voting systems that promote trust and social inclusion.
The RCS group brings together a diverse team of researchers and engineers who collaborate on national and international projects. We aim to create technologies that not only push the boundaries of innovation but also make a positive impact on society.
Key Research Areas
- Autonomous Robotic Systems: Intelligent robotic systems are being designed and deployed in order to build systems capable of operating in dynamic, real-world environments. Focus areas include: navigation, manipulation, perception, human-robot collaboration and swarm intelligence.
- AI & Federated Learning: Data-driven models are being developed in order to support decision-making in complex domains such as healthcare and manufacturing. The group explores federated learning, edge AI and collaborative model training for secure, real-time decision-making.
- Generative AI for Social Services: Large Language Models (LLMs) are leveraged in order to build multilingual, assistive chatbots that support public-facing services and promote accessibility and inclusion.
- Blockchain for Transparent Governance: The group designs decentralized platforms for policy recommendation, community decision-making and public accountability, ensuring secure, tamper-proof participation and data integrity.
- Supply Chain Trust via Distributed Ledgers: The group focuses on the development of blockchain-based systems that track goods and services across supply chains, ensuring provenance, anti-counterfeit measures and regulatory compliance.
Technological Domains
Our group focuses on a diverse and evolving set of technology domains, combining foundational expertise with exploration into emerging areas. Below is a high-level overview of our technical landscape:
- Robotics & Embedded Systems: We develop intelligent robotic systems capable of sensing, decision-making and autonomous action in complex environments. Our research covers the entire robotics stack, from low-level control to high-level interaction and user experience. More specifically, we focus on:
- Autonomous Robotic Systems for navigation, manipulation and task execution in unstructured environments
- Human-Robot Interaction (HRI) and Swarm Interaction (Robot interaction)
- Human-Centered Design – prioritizing usability, ethics, and user experience in robotic systems
Concerning the technologies, we make use of ROS2, Django, React, Gazebo, OpenCV
- Blockchain & Decentralized Systems: Our group builds blockchain-based systems that ensure trust, transparency, and decentralization in critical domains like governance and asset tracking. The technologies adopted in this domain include: Hyperledger Fabric, Hyperledger Besu, Hyperledger Aries, EVM-compatible chains, Solidity, IPFS and Node.js
- Artificial Intelligence & Distributed Learning: AI powers our systems across domains such as healthcare, robotics and public services. We focus on both centralized and privacy-preserving distributed AI. The tools and frameworks employed include: PyTorch, TensorFlow, Scikit-learn, Flower.
- Generative AI & Language Technologies: Our group makes use of LLMs to build conversational agents and tools that support multilingual, context-aware communication. The technology stack consists of LangChain, LangGraph, Hugging Face Transformers and FastAPI.
- Full-Stack Application Development & Deployment: Our group designs, builds and deploys end-to-end software solutions that integrate frontend, backend and infrastructure components. Our implementation relies on these technologies and frameworks: Quarkus, React, React Native, PostgreSQL, MongoDB, DOcker, CI/CD, (GitHub Actions, GitLab CI), Kubernetes
Specialized Expertise
- Human-Centered Robotics: We use methodologies from human-centered design and cognitive science to develop cognitive interfaces and enhance human-robot interaction (HRI). We also specialize in deploying robotic solutions tailored to the needs of small and medium-sized enterprises (SMEs), focusing on cost-effective automation, ease of integration, and adaptability to existing workflows.
- Blockchain for Trust, Inclusion and Transparency: We apply blockchain technologies to build decentralized systems that enhance transparency and social equity. Our work includes the development of digital wallets leveraging Self-Sovereign Identity (SSI) principles, enabling users to manage their identity and credentials independently. We create and issue Verifiable Credentials (VCs) to support policy recommendation systems, enabling trusted, data-driven insights in areas such as social services and digital governance.Our implementations follow open standards such as W3C Verifiable Credentials, Decentralized Identifiers (DIDs), and DIDComm protocols for secure communication. Additional focus areas include decentralized voting, supply chain traceability, and digital inclusion platforms, with validated use cases in EU-funded projects and community-led governance initiatives.
- AI for Distributed, Real-Time and Privacy-Conscious Systems: We specialize in developing AI models that operate across edge and federated environments—ensuring real-time performance and data privacy. Our expertise includes federated learning, edge deployment strategies, and distributed optimization for autonomous systems. This work has been deployed in manufacturing applications, with the focus on process monitoring and steering for EU-funded projects.
Description
AI4Gov unveils the potentials of AI and Big Data technologies for developing evidence-based innovations, policies, and policy recommendations to harness the public sphere, political power, and economic power for democratic purposes. AI4Gov will introduce solutions and frameworks towards a two-fold sense, to facilitate policymakers on the development of automated, educated and evidence-based decisions and to increase the trust of citizens in the democratic processes and institutions.Key Contributions
UBITECH’s RCS team centers on integrating AI and blockchain technologies into a unified, secure, and explainable platform for evidence-based policymaking. RCS team will lead the integration of AI tools (e.g., predictive models, explainable AI, bias detection) as modular, on-demand services within the AI4Gov platform and ensure seamless interconnectivity through collaborative tools and a robust integration plan. Furthermore, RCS team will develop a decentralized, permissioned blockchain infrastructure, enabling secure data sharing, consent management, data provenance, and smart contract-based governance mechanisms. It will also design the Data Governance Framework (DGF) to ensure compliance with regulations, data quality, and ethical data usage throughout the platform lifecycle. Finally, RCS team will contribute to the exploitation strategy, focusing on AI4Gov’s commercialization, reuse of policy models and datasets, and provision of AI and data services within the GovTech ecosystem.
Description
MARS enables SMEs to access advances in the field of AI-driven digital manufacturing processes and enter into geographically distributed process chains, by developing Industry4.0 technologies including digital twins, bio-intelligent production devices, data-driven manufacturing process models, blockchain technology for traceability and securitization, multi-agent based manufacturing planning, multi-criteria intelligent optimization especially addressing environmental footprint.Key Contributions
UBITECH's RCS team leads the design of a common semantic model to represent key manufacturing process concepts and defines the reference architecture for applying federated learning in distributed manufacturing environments. Their work enables the development and deployment of decentralized AI solutions that enhance process planning, optimization, and control in zero-defect manufacturing. By leveraging federated learning, the RCS team ensures that local AI models can be collaboratively trained and aggregated without sharing sensitive data, enabling privacy-preserving knowledge exchange. These models will support process optimization by evaluating production stability and recommending control parameter adjustments to improve cost-efficiency and resource usage. Ultimately, the RCS team’s contributions form the backbone of a scalable, interoperable AI-driven framework for next-generation manufacturing systems.
Description
ARISE aims to advance automation in renewable energy and agriculture by developing a reconfigurable robotic system capable of performing complex manipulation tasks. Combining mobile robotic arms, soft adaptive end-effectors, advanced perception, and learning from human demonstrations, ARISE will enable intelligent, flexible automation. Its AI-driven modules will support scene understanding, semantic mapping, and real-time planning. The system will be validated through real-world tasks in solar and hydroponic farms, addressing labor shortages while boosting efficiency and adaptability.Key Contributions
UBITECH's RCS team is leading the definition of ARISE’s hardware and software architecture, ensuring seamless integration of robotic modules, sensor interfaces, and Edge-AI capabilities within the system. They are also responsible for deriving functional requirements by analyzing complex, long-duration manipulation tasks across diverse use cases such as solar panel maintenance and lettuce harvesting. Additionally, the RCS team is developing and deploying the Knowledge Representation module, managing software interfaces, and supporting integration with cloud-native MLOps platforms for efficient edge deployment. Their work also includes overseeing system-level networking protocols and ensuring compatibility with platforms like AI4EU, facilitating modular, scalable, and explainable AI-driven robotic solutions.
Description
XR5.0 will develop and validate a new, person-centric XR (Extended Reality) paradigm tailored to Industry 5.0, combining advanced AI and human-centered digital twins. Focused on European values and worker well-being, the project will enable personalized, ergonomic XR applications for training, maintenance, design, and assembly in real manufacturing environments. XR5.0 integrates cutting-edge AI technologies like explainable AI, generative AI, and neurosymbolic learning, and will deliver high-TRL solutions ready for commercialization, supported by a growing stakeholder community and the EU XR platform.Key Contributions
As the leader of the Work Package entitled "Specifications, Architecture and EU XR Platform Integration", UBITECH's RCS team is responsible for overseeing the successful execution of all tasks within this work package. This includes the definition of reference XR scenarios, the technical specifications of the tools, the design and implementation of open APIs, DevOps procedures, deployment strategies and the seamless integration of XR5.0 with the EU XR platform, ensuring smooth integration and compliance. Beyond our leadership responsibilities, our group is directly executing key tasks related to the development of the Reference Architecture and the integration with the EU XR platform, ensuring both the conceptual design and technical implementation align with project-wide goals. Moreover, RCS group plays a key role in ensuring compatibility with industrial standards such as RAMI 4.0, ISO/JTC, OpenXR, XRSI,IIRA, etc.
Description
EVOSST aims to enhance the effectiveness and understanding of social services across the EU by developing advanced, life-course impact assessment models. Covering areas such as healthcare, education, childcare, and inclusion, the project supports the EU's goals for social cohesion and sustainable development. EVOSST integrates well-being metrics and digital technologies to improve service delivery and user experience, aligning with the Digital Education Action Plan and the European Pillar of Social Rights. The project seeks to inform better policies by transforming how the long-term impacts of social services are measured.Key Contributions
UBITECH's RCS team is leading advanced data analysis efforts in EVOSST, applying statistical methods and visual analytics to extract meaningful insights on the lifecycle impacts of social services. They contribute to building a robust evidence base for the SROI framework by aligning data collection strategies with stakeholder needs and national datasets. Their work also supports the integration of a Social Service Well-being Metric, ensuring that economic, social, and environmental dimensions are captured holistically in evaluations. The team is involved in the design and risk management of a scalable, AI-enabled SROI framework, adaptable to diverse settings. Furthermore, they participate in pilot testing of AI and immersive technologies—such as virtual reality reskilling platforms, adaptive learning systems, and multilingual assistants—measuring their real-world impact on accessibility, education, and service delivery for vulnerable groups.
Description
AROGI is an innovative robotics project dedicated to transforming logistics for small and semi-structured spaces like hospitals, hotels, and compact warehouses. By introducing autonomous robots powered by a smart Task Management System (TMS), AROGI automates material transport, boosting productivity, enhancing safety, and significantly reducing logistics costs. Tailored for environments where traditional logistics solutions are impractical, AROGI offers an affordable, scalable solution to streamline operations and free up valuable human resources.Key Contributions
UBITECH’s RCS team focuses on the design and development of a flexible task codification scheme (TCS) that forms the backbone of the system's adaptability across diverse commercial environments. RCS team leads the definition of the reference architecture, the development of the user interfaces, and the task specification software, ensuring seamless integration with external logistics and business systems through standardized interfaces and ontologies. Additionally, RCS team is responsible for implementing core robot control functionalities, including task planning, motion control, SLAM, and system coordination using ROS. In the final phase, RCS team supports the integration, evaluation, and demonstration of the complete AROGI platform in real-world scenarios, contributing to the validation of its technical innovations and business value.
Description
HospAItal aims to leverage and transform the way patients in intensive care units (ICUs) are monitored, where it will allow for core facilities to be shared and linked composing smart services for healthcare professionals, patients, information system managers, and health organization administrations, incorporating a set of AI-based personalized healthcare services.Key Contributions
UBITECH's RCS team is actively involved in driving innovation management within HospAItal by leveraging creative methodologies and IPR tools to ensure the efficient evolution of the platform throughout the project lifecycle. They lead the technical groundwork through a thorough analysis of existing AI, ML, and IoT healthcare solutions, evaluating their integration potential into the platform via comparative testing and benchmarking. The team also contributes to defining the semantic data models and interoperability layers that combine clinical entities with smart technologies for secure, smooth service delivery. In addition, they are developing an AI-powered diagnostic tool for early sepsis detection using real-world ICU data, integrating reinforcement learning for precise sedation dosage predictions. To support agile development, UBITECH is setting up a CI/CD environment and a collaborative integration framework that ensures seamless deployment and service interoperability across the HospAItal ecosystem.
Description
The TraCEREAL project is dedicated to investigating how Blockchain technology, in conjunction with advanced IoT capabilities, can contribute to the establishment of resilient supply-chain operations within Cyprus. The project's objective is to develop and showcase a functional prototype system composed an intelligent algorithmic framework, seamlessly integrated with IoT technology, that can assist policymakers and industry stakeholders in constructing more resilient cereal supply chains tailored to the specific needs of Cyprus.Key Contributions
UBITECH's RCS team leads the design of the TraCEREAL methodology and platform architecture, mapping out stakeholder workflows and developing scalable, interoperable, and secure technical specifications using modular, open-source components. They are building a rich knowledge graph that fuses structured and unstructured data, including blockchain-derived information, to support traceability and intelligent decision-making. Their work on argumentation mining employs advanced ML and clustering techniques to extract and structure arguments from large text corpora, aiding policy and strategy formulation. Additionally, they oversee the integration of open-source APIs, applications, and data sources into the TraCEREAL ecosystem, ensuring robust testing, data privacy, and seamless system interoperation. Finally, they contribute to evaluating the business impact of the solution, assessing its economic and strategic value at both individual and national levels.
Description
inGOV enables European public authorities to co-create user-friendly Integrated Public Services accessible via mobile devices to all, particularly the disadvantaged, resulting in increased adoption, efficiency, effectiveness, trust & satisfaction. inGOV delivers a comprehensive IPS Holistic Framework that includes IPS governance; IPS agreements between stakeholders; stakeholders involvement; migration guidelines; and an agile roadmap, addressing all legal, cultural and managerial challenges.Key Contributions
UBITECH's RCS team leads the iterative development of the inGOV ICT architecture and tools, delivering three progressively refined releases over the course of the project. The architecture is built around four key pillars, integrating knowledge graphs, linked data technologies, stakeholder coordination mechanisms, mobile applications, and chatbot-based virtual assistants. The team emphasizes citizen-centric design by embedding digital services across mobile and social media platforms, tailoring implementations to local needs. Throughout all development phases, they apply agile and design science methodologies, ensuring continuous alignment with evolving governance models, user feedback, and pilot evaluations.
Description
GLASS caters for a European Common Services Web, bringing closer citizens, businesses & governments, introducing a citizen-centric e-gov model that enables participation in a data exchange & service delivery network that is by design digital, efficient, cost-effective, interoperable, cross-border, secure and promotes the once-only priority. GLASS delivers a single sign-on Wallet as a Service framework managing multiple services provided by DApps, supported by distributed ledgers & file storage.Key Contributions
UBITECH's RCS team leads several key technical components of GLASS, contributing to user-centric design, security, and interoperability. They define technical, operational, and interoperability requirements to ensure seamless integration across the GLASS distributed infrastructure. UBITECH also develops the user interface for the Wallet-as-a-Service (WaaS), supporting multi-identity and multi-key management through both mobile and web applications. Furthermore, they establish a decentralized applications (dapps) ecosystem and secure blockchain-based communication channels, focusing on privacy, scalability, and usability for both developers and end-users. Their work enables a trustworthy, accessible, and customizable cross-border e-Government service platform.
Description
TheFSM aims to deliver an industrial data platform that will significantly boost the way that food certification takes place in Europe. The platform will facilitate the exchange and connection of data between different food safety actors, who are interested in sharing information critical to certification. The project is going to accelerate the pace by which this type of certification bodies (in Europe and beyond) adopt digital innovation and offer data-driven services.Key Contributions
UBITECH's RCS team plays a central role in the design, development, and integration of the TheFSM platform, coordinating the architecture and core security components. They lead the development of the platform’s reference architecture, user identity and access control mechanisms, and secure data storage and communication layers. RCS team also implements key elements of the blockchain-powered Smart Contracting Layer, including brokerage workflows and machine-readable legal automation. In addition, they oversee testing, quality assurance, and technical verification to ensure robust interoperability with external agri-data platforms and smooth integration of front-end applications. Their contributions are foundational to building a secure, decentralized, and legally sound data-sharing ecosystem in the agri-food domain.
Description
Search and Rescue delivers a highly interoperable, modular open architecture platform for first responders, easily incorporating next generation R&D and COTS solutions possibly formulating the future disaster management system, as well as a wider range of decisional support features and monitoring systems, providing first responders with an effective and unified vision of the dynamic changes going on during event’s lifetime and the capabilities and resources currently deployed in the field.Key Contributions
The RCS team plays a key role in enhancing situational awareness and emergency response through advanced data integration and AI-driven analytics in the S&R project. They lead the development of the Situation Awareness Model, enabling real-time decision-making for first responders using semantic knowledge structures, VR interfaces, and building information modeling (BIM). RCS team also contributes to deep learning-based human/object detection from UAV imagery and multi-sensor fusion, increasing in-disaster scene comprehension. Additionally, RCS team supports the integration of mature technologies into the system architecture and contributes to the platform's reference and communication design, ensuring interoperability and scalability. Their efforts collectively aim to improve operational coordination, safety, and efficiency in disaster response scenarios.
Description
BIMERR delivers a Renovation 4.0 toolkit supporting throughout the renovation process of existing buildings from project conception to delivery, comprising tools for the automated creation of enhanced building information models, a renovation decision support system to aid the designer in exploring available renovation options, and a process management tool that will optimize the design and on-site construction process toward optimal coordination and minimization of renovation time and cost.Key Contributions
The RCS team led the technological development of the BIMERR system, designing its modular and interoperable architecture. They developed the interoperability framework and middleware for seamless data exchange, and specified the Semantic Modelling tool to align diverse data models. They also ensured secure, GDPR-compliant data handling. Their work formed the backbone of a cohesive and scalable digital renovation platform.
Description
UPTIME reframes predictive maintenance strategy in a systematic and unified way so as to fully exploit the advancements in ICT and maintenance management by examining the potential of big data in an e-maintenance infrastructure, to deliver novel e-maintenance services and tools to support the daily work of maintenance engineers as well as the overall maintenance management with the aim to optimize in-service efficiency.Key Contributions
The RCS team developed and maintained the software infrastructure for the UPTIME platform, implementing version control, continuous integration, and quality assurance tools. They led the integration and testing cycles, delivering both initial and final platform releases. RCS also supported data acquisition and manipulation across pilot cases, ensuring real-time data flow and interoperability. For the MAILLIS pilot, they set up the ICT infrastructure, deployed the UPTIME platform, and integrated it with existing systems, tailoring dashboards and tools to user roles.
Description
ChildRescue explores patterns of interaction & awareness during the missing children investigations, leveraging the untapped potential of open-social-linked data to augment the background information of missing children through multi-layer (personal, psychological, social & activity) profiling & predictive analytics, respecting & protecting privacy & personal data, providing evidence-based insights for the network effect’s impact to response organizations and allow them make informed decisions.Key Contributions
The RCS team played a central role in designing the ChildRescue platform, ensuring privacy by integrating advanced data anonymization and protection techniques. They defined the platform's architecture, enabling interoperability and secure interaction with external systems, and supported the development of APIs and integration logic. RCS also led the mobile app development using cross-platform technologies, aligning with the platform’s iterative development cycles. They contributed to technical testing, quality assurance, and continuous integration, ensuring a robust, validated system. Additionally, they supported the open data strategy, promoting knowledge sharing and reuse of project outcomes.Decentralized Identity Wallet
This artifact presents an Identity Wallet application built using the Hyperledger Aries framework, leveraging Verifiable Credentials (VCs) to enable secure and privacy-preserving user verification. The wallet is based on blockchain technology and advanced cryptographic methods, allowing identity data to be securely shared with service providers while disclosing only the necessary information. This approach empowers individuals with self-sovereign identity (SSI), granting them full control over their personal data and enhancing both privacy and security. Designed to support a decentralized voting system, the wallet fosters trust among stakeholders without the need for a centralized authority. By utilizing VCs for credential issuance, presentation, and verification, the system ensures that only eligible and authenticated users can vote—boosting transparency and integrity. The solution integrates key tools and libraries such as Aries Cloud Agent, Aries Askar, and AnonCreds for credential management and DID communication, while employing zero-knowledge proof protocols and homomorphic encryption algorithms to protect user privacy and vote confidentiality. Built upon the Hyperledger Aries and Indy frameworks, this system also follows the W3C Verifiable Credentials and Decentralized Identifiers (DID) standards, demonstrating a secure and standards-compliant implementation of decentralized identity principles in a real-world governance scenario.Supply Chain Traceability System
This artifact presents a blockchain-based supply chain traceability system designed to ensure data transparency, product authenticity, and trust among stakeholders. Built on the Hyperledger Fabric framework, the system leverages smart contracts (chaincode) to immutably record supply chain events and transactions, guaranteeing data integrity at every stage. The backend utilizes Node.js with the Fabric Gateway SDK for seamless interaction with the blockchain network, while Apache Kafka enables real-time data streaming and synchronization between distributed components. By incorporating distributed ledger technology (DLT), smart contracts, and Internet of Things (IoT) integration, the system automates processes, enforces agreements without intermediaries, and captures real-time environmental data—such as temperature and location—which is securely written to the blockchain. This decentralized, event-driven architecture ensures that each participant contributes verified, tamper-proof data that cannot be altered or manipulated. As a result, the system provides scalable, trustworthy, and auditable supply chain management, significantly reducing the risk of fraud or counterfeiting while reinforcing confidence in product authenticity and provenance.Federated Learning for Distributed Manufacturing
Our Federated Learning (FL) framework enables manufacturing sites to collaboratively train AI models without sharing sensitive data, ensuring privacy and GDPR compliance. It features personalized model layers to adapt the global model to local data, improving accuracy in non-IID manufacturing environments. The system supports real-time process monitoring to guarantee quality control across distributed production units. It advances industrial AI by enabling secure, scalable, and collaborative intelligence at the edge. The framework is built using Flower for orchestrating federated learning processes, with PyTorch as the core machine learning library for model development and training. To ensure secure and decentralized model weight storage, the system leverages IPFS (InterPlanetary File System), promoting data traceability and resilience. This combination of technologies allows for flexible deployments across diverse manufacturing nodes, while maintaining data sovereignty and system robustness.AI Models for 3D Ultrasound Follicle Analysis (AI Models for Predictive 3D Ovarian Follicle Monitoring in IVF)
An AI-powered system specialized in the automated analysis of 3D ultrasound data for accurate measurement of ovarian follicles in women with high ovarian response during IVF. It supports precise determination of oocyte maturation timing, helping to minimize the risk of Ovarian Hyperstimulation Syndrome (OHSS) and enabling safer, more personalized fertility treatments. The system includes a custom Flask-based application designed to deliver model outputs to clinicians in a usable format. To address the same prediction task from different methodological perspectives, we developed and evaluated a range of AI models, including XGBoost, Scikit-learn pipelines, and Keras-based deep learning models. This ensemble approach supports robust performance comparisons and allows for model selection based on clinical context, interpretability, or deployment constraints.Digital Platform for Issuance and Renewal of Disability Discount Cards
A digital service pilot for automating the issuance and renewal of public transportation discount cards for disabled citizens in the Region of Thessaly, aiming to simplify access, reduce bureaucracy, and ensure inclusive mobility services. The platform was developed, focused on improving accessibility and user experience for people with disabilities and their caregivers. The solution consists of a React Native mobile application, which allows users to submit required documents, track their application status, and receive a valid digital discount card. A complementary React web application supports government bodies in reviewing and validating applications via a secure, role-based system. The backend is built using Quarkus, offering a high-performance and lightweight Java framework ideal for cloud-native deployments, and is connected to a MongoDB database for handling both structured and unstructured data. To ensure secure and interoperable authentication, the platform integrates Keycloak for identity and access management and offers support for Taxisnet authentication via SOAP-based services, aligning with national e-government standards. These features guarantee both secure user access and seamless interoperability with existing public administration systems.Web-Based Tourism Overnight Stay Tax Service
A digital pilot service that streamlines the declaration and management of tourism overnight stay taxes in Lower Austria, providing an integrated and user-friendly web interface for accommodation providers and local authorities. The system improves transparency, efficiency, and compliance in regional tax administration. It provides a user-friendly, secure interface for businesses to submit and manage tax declarations, while also offering authorities tools for auditing, reporting, and analytics. The platform is built using React for a responsive and accessible front-end experience, Quarkus as the high-performance Java-based backend framework. The system is underpinned by a Microsoft SQL Server database, providing enterprise-grade reliability, transactional consistency, and seamless integration with existing public sector IT infrastructures. The entire system is containerized and deployed on a Kubernetes cluster, ensuring scalability, high availability, and maintainability in production environments. This modern technology stack ensures a seamless user experience, high availability, and easy integration with existing government systems. The system supports role-based access control, automated notifications, and report generation to simplify workflows for both private and public sector actors.Culturally Sensitive Multilingual AI Chatbot for Social Service Accessibility
This AI-powered chatbot is designed to support migrant populations in multicultural urban communities by providing multilingual and culturally sensitive access to social services. It leverages Retrieval-Augmented Generation (RAG) and state-of-the-art foundation models to deliver accurate, real-time responses based on both conversational context and reliable information sources. The system is built using a modern AI stack that includes LangChain, LangGraph, Hugging Face for integrating powerful multilingual language models, and FastAPI for scalable deployment. By supporting multiple languages, including English, Arabic, French, and Ukrainian, the chatbot breaks down communication barriers between migrants and service providers, ensuring equitable access to essential services like healthcare, legal aid, housing, and education. Cultural sensitivity mechanisms are embedded into the interaction layer to recognize and adapt to different cultural norms, promoting trust and comfort in vulnerable user groups. Developed as part of a public sector innovation initiative, the chatbot is designed for 24/7 availability, making it a scalable, inclusive tool for modern urban social support systems.Multi-Robot Delivery and Transportation System with Autonomous Navigation and Web-Based Task Orchestration
A scalable system for autonomous delivery and transportation using a fleet of robots equipped with SLAM-based navigation and built on a ROS 2 architecture for modular, distributed control. The system features a centralized, web-based platform for real-time task assignment, monitoring, and coordination, leveraging tools such as rosbridge and WebSockets for seamless communication between the web frontend and ROS-based robot backend. It supports deployment in both simulated environments (e.g., Gazebo) and on physical robots, with containerized components (Docker, Docker Compose) enabling reproducibility, scalability.Group Leader
Dr Xanthi S. Papageorgiou, (Senior Researcher & Group Leader)
Expertise: Intelligent Robotic & Autonomous Systems, Human-Robot Interaction, Robot Control & Decision Systems, Robotic Motion & Task Planning
Short Bio
Dr Xanthi S. Papageorgiou is the Head of Robotics and Cognitive Systems Unit at UBITECH - The Ubiquitous Technologies Company, Athens, Greece and UBITECH LIMITED, Limassol, Cyprus. She holds a Mechanical Engineering Degree from National Technical University of Athens (June 2003) and Ph.D. (July 2009) on the subject of Motion Tasks on Neuro-Robotic Systems from the Control Systems Laboratory of the School of Mechanical Engineering of NTUA, where she worked on a number of research projects (2002-2009). She was a Research Associate at the Department of Embodied Interaction and Robotics at the Institute for Language and Speech Processing (ILSP), at the Athena Research Center (“Athena”; R.C.) (2018-2021). Also, she was a Senior Research Fellow in Robotics Control and Decision Systems (RCDS) Laboratory, Department of Mechanical Engineering and Materials Science and Engineering (MEM), at the Cyprus University of Technology (CUT) (2018-2020). She currently also serves as an Assistant Professor in the School of Engineering, Department of Product & Systems Design Engineering (DPSD) at the University of the Aegean (2024 - today). She was an adjunct Assistant Professor in the School of Mechanical Engineering (MECH) at the National Technical University of Athens (NTUA) (2022-2024), and in the Department of Physics, at the National and Kapodistrian University of Athens (2019-2021). Furthermore, she was a Post-Doctoral Researcher in the Intelligent Robotics and Automation Laboratory, School of Electrical and Computer Engineering at the NTUA (2013-2018). She joined the Technological Educational Institute of Piraeus, School of Technological Applications, as an Adjunct Lecturer on Digital Control and Microcontrollers (2008-2015). Her main research interests include neuro-robotics, human/robot interaction, neuroscience, and rehabilitation, as well as motion tasks, force control, compliant, adaptive, and optimal control methods, and their applications to robotic systems, eGovernance, Data Platforms, Traceability, Supply Chain, Food Safety. She has authored and co-authored more than 70 scientific publications in international journals and conference proceedings. She has also participated in several national and international research programs. She currently is a reviewer in several international journals and conferences. She is a member of IEEE, IEEE Robotics & Automation Society, IEEE Control Systems Society, and the Technical Chamber of Greece.
[LinkedIn] [Google Scholar] [ORCID]
Key Team Members
Μr. Athanasios Giannakopoulos (Senior Software Architect)
Expertise: Artificial Intelligence, Machine Learning, Generative AI, Blockchain Technologies, Full-Stack development
Short Bio
Mr. Athanasios Giannakopoulos is a Software Engineer at the Robotics and Cognitive Systems Unit at UBITECH Ltd. He received his B.Sc. degree in Economics and an M.Sc. degree in Computer Science from the Athens University of Economics and Business. He is also currently pursuing a second B.Sc. degree in Informatics at the same institution, as well as a Master’s degree in Quantum Computing and Quantum Technologies through the joint international postgraduate program offered by the Democritus University of Thrace (DuTH) and the National Centre for Scientific Research "Demokritos". His first Master's thesis, “Elastic Scaling for Apache Kafka with Deep Reinforcement Learning” was completed in January 2021 and published in a well-regarded conference. His work spans multiple domains, including AI, GenAI, Blockchain, and Full-Stack development.
[LinkedIn] [Google Scholar] [ORCID]
Μr. Nikos Kalantzis (Software Engineer)
Expertise: Blockchain Technologies, Cybersecurity, Identity and Access Management, Cryptography, Supply Chain System, Full-Stack Development, Integration & Deployment Automation
Short Bio
Mr. Nikos Kalantzis is Software Engineer at the Robotics and Cognitive Systems Unit at UBITECH Ltd., where he is involved in R&D projects with main focus on Blockchain technologies. His work includes developing Smart Contracts, full stack decentralized apps (dApps) and Distributed Ledger software based in Hyperledger Fabric and other DLT platforms. He received his B.Sc. in Informatics (2017) and M.Sc. in Information Systems Development and Security (2022), with specialization in Cybersecurity & Critical Infrastructure Protection, from the Department of Informatics at the Athens University of Economics and Business (AUEB). His Master’s thesis explored the integration of Blockchain and IoT technologies to enhance the integrity of data in Supply Chain Management Systems. His expertise covers a range of domains including secure Blockchain architecture, decentralized identity, access management and applied cryptography, along with practical experience in containerization with Docker, orchestration with Kubernetes, automated deployment pipelines.
Mr. Nikolaos Tousert (Research Software Architect)
Expertise: Enterprise Architecture, Software Engineering, Embedded Systems, Interdisciplinary Research, European R&D Projects, Industry 5.0, Intelligent Transportation Systems, Crisis Management, Bioengineering Applications, Supply Chain Innovation, Robotics, Blockchain Technologies, Web Applications, Artificial Intelligence, Edge Computing, Digital Twins, Software Design Patterns, Agile Development, Cloud-Native Applications, IoT Systems
Short Bio
Mr. Nikolaos Tousert (male) holds a degree in Electrical and Computer Engineering (ECE) from the National Technical University of Athens (NTUA). He has more than seven years of experience as a software engineer in European research projects, contributing to diverse domains such as bioengineering, crisis management, intelligent transportation systems, embedded systems, Industry 5.0. Currently, he works as a Research Software Architect at UBITECH, focusing on Industry 5.0, supply chain innovation and robotics. His role involves designing and developing cutting-edge software solutions tailored to these sectors. His technical expertise includes software development and design, embedded systems, enterprise architecture and a wide range of programming languages and frameworks. He has authored numerous publications in peer-reviewed journals and international conferences. His research and professional interests include blockchain, robotics and web applications, as well as emerging technologies such as artificial intelligence, edge computing and digital twins.
Dr Anastasia-Dimitra Lipitakis (Research Projects Delivery & Fundraising Manager)
Expertise: Computational Science, Applied Mathematics, and Artificial Intelligence
Short Bio
Dr. Anastasia-Dimitra Lipitakis is a Research Projects Delivery & Fundraising Manager at the Robotics and Cognitive Systems Unit at UBITECH Ltd. She received her B.Sc. degree in Mathematics and Statistics from the University of Cyprus and an M.Sc. degree in Applied Mathematics and Artificial Intelligence from the University of Patras, Greece. She is also having her PhD degree in Computational Science and Applied Mathematics from the Department of Informatics and Telematics of Harokopio University of Athens, Greece. She has more than 5 years’ experience in project management, proposal writing and research activities of national and EU and National funded projects. She is responsible for technical leadership in work packages and deliverables, architectural design of research prototypes, and engagement in scientific dissemination activities. She has several publications in international conference proceedings and journals. She has participated as a researcher in numerous research projects.
[LinkedIn] [Google Scholar] [ORCID]
Mr. Dimitrios Kavroulakis (Robotics Research Associate)
Expertise: Robotics & Autonomous Systems, Human-Robot Interaction, Robotic Motion & Task Planning, Real-time Robot Control, Web Application Design and Development
Short Bio
Mr. Dimitrios Kavroulakis is a Robotics Research Associate at UBITECH, since August 2021. He received his diploma in Electrical and Computer Engineering from the Technical University of Crete, in March 2021. His Diploma Thesis on the “Visual Recognition and Writing with the NAO Humanoid Robot” completed in December 2020. He has been actively involved in the development, support, maintenance of Department’s systems and services & Optimised existing systems, improving their performance at the Hellenic Army, in March - July 2021. Additionally, he has participated in the Robotic team Kouretes of the Technical University of Crete, in 2019 - 2020. Finally, Dimitrios Kavroulakis was Research Intern at the SenseLab of the Technical University of Crete, in July - August 2016.
Μr. Konstantinos Tzelaptsis (Software Engineer)
Expertise: Mobile-Web applications
Short Bio
Mr. Konstantinos Tzelaptsis (male) is a Software Engineer at the Robotics and Cognitive Systems Unit at UBITECH Ltd. He received his BSc from the Informatics Engineering and Telecommunications Department of the Polytechnic School of the University of Western Macedonia. His Diploma Thesis was based on the ECG-ESP viewer, a health web application in November 2013. He specializes in websites and web applications development while he has gained experience from several freelance jobs for businesses, associations, individuals as well as for the public sector. Moreover, during 2008 he was a member of a team developing an online food ordering platform. Since 2019 he has been a member of the Greek Technical Chamber with a professional license as an electronic engineer.
Recent Highlights
Publications:
- Xanthi S. Papageorgiou, Anastasia-Dimitra Lipitakis, Dimitrios Kavroulakis, Athanasios Giannakopoulos, “A Modular Architecture for Autonomous Robotic Logistics in Semi-Structured Environments”, Proceedings of the 2025 IEEE 11th International Conference on Control, Decision and Information Technologies, 15-18 July, 2025, Split, Croatia.
- Nikolaos Tousert, Anastasia-Dimitra Lipitakis, Athanasios Giannakopoulos, Dimitrios Ntalaperas, Athanasios Kiourtis, Argyro Mavrogiorgou, Xanthi S. Papageorgiou, “Human-Centric AI-Enabled Extended Reality Reference Architecture for Industry 5.0”, Proceedings of the 2025 IEEE 11th International Conference on Control, Decision and Information Technologies, 15-18 July, 2025, Split, Croatia.
- Konstantinos Mavrogiorgos, Shlomit Gur, Nikolaos Kalantzis, Konstantinos Tzelaptsis, Xanthi S. Papageorgiou, Andreas Karabetian, Georgios Manias, Argyro Mavrogiorgou, Dimosthenis Kyriazis, Celia Parralejo Cano, “Combining Explainable Artificial Intelligence (XAI) with Blockchain towards Trustworthy Data-driven Policies”, 2nd Workshop on Next Generation IoT and AI systems for Trusted, Human-Centered Intelligence, Co-located with IEEE 21st Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT 2025), Tuscany (Lucca), Italy, June 9-11, 2025.
- Xanthi S. Papageorgiou, Dimitris Kavroulakis, Dimitris Ntalaperas, Thanassis Bouras, “A Task Restricted Hierarchical Control Scheme Facilitating Small Logistics”, Proceedings of the 2024 IEEE International Conference on Robotics and Automation, Workshop: 2nd Workshop on Mobile Manipulation and Embodied Intelligence (MOMA.v2), 13 - 17 May 2024, Yokohama, Japan.
- Xanthi S. Papageorgiou, Danai Vergeti, Dimitris Ntalaperas, “Motion Tasks Representation: Extracting Knowledge from Human Experts”, Proceedings of the 2023 IEEE International Conference on Robotics and Automation, Workshop: RAP4Robots - Effective representations, abstractions, and priors for robot learning, 29 May – 2 June 2023, London, UK.
- Charithea Stylianides, Andria Nicolaou, Waqar Aziz Sulaiman, Christina-Athanasia Alexandropoulou, Ilias Panagiotopoulos, Konstantina Karathanasopoulou, George Dimitrakopoulos, Styliani Kleanthous, Elena Politi, Dimitris Ntalaperas, Xanthi S. Papageorgiou, Fransisco Garcia, Zinonas Antoniou, Nikos Ioannides, Lakis Palazis, Anna Vavlitou, Marios S. Pattichis, Constantinos Pattichis, Andreas S. Panayides, AI Advances in ICU with an Emphasis on Sepsis Prediction: An Overview. Mach. Learn. Knowl. Extr. 2025, 7, 6. https://doi.org/10.3390/make7010006
- Athanasios Kiourtis, Argyro Mavrogiorgou, Georgios Makridis, Dimosthenis Kyriazis, John Soldatos, Georgios Fatouros, Dimitrios Ntalaperas, Xanthi S. Papageorgiou, Bruno Almeida, Joana Guedes, Pedro Maló, Jorge Oliveira, Sebastian Scholze, Antonio Rosinha, Joaquim Reis, Matteo Falsetta, "XR5.0: Human-Centric AI-Enabled Extended Reality Applications for Industry 5.0", 2024 36th Conference of Open Innovations Association (FRUCT), Lappeenranta, Finland, 30 October - 01 November 2024, pp. 314-323, DOI: 10.23919/FRUCT64283.2024.10749931.
- George Manias, Spiros Borotis, Charalampos Chatzimallis, Tanja Zdolsek Draksler, Alenka Gucek, Fabiana Fournier, Andreas Karabetian, Dimitris Kotios, Matej Kovacic, Danai Kyrkou, Lior Limonad, Konstantinos Mavrogiorgos, Dimitris Ntalaperas, Xanthi S. Papageorgiou, Dimosthenis Kyriazis, “Fostering Fundamental Human Rights and Trustworthiness though the Utilization of Emerging Technologies: the AI4Gov Platform”, Global Conference On AI And Human Rights, 13 - 14 June 2024, Facultyof Law, University of Ljubljana, Slovenia.
Collaboration & Partnerships
Academic & Research Collaborations
- Manufacturing Technology Lab (MTL) - National Technical University of Athens
- Technical University of Darmstadt (TuDa)
- University of Western Macedonia (UOWM)
- University of Piraeus Research Center (UPRC)
- École nationale supérieure d'arts et métiers (ENSAM)
- Manufacturing Technology Institute (MTI) - RWTH Aachen University
- Inspire AG (ETH)
Industry Engagement
For collaboration opportunities and other inquiries, contact us at [email protected]
