The project aims to develop new machine learning approaches for the Girona1000 AUV, that integrates side-scan sonar with a dual-camera optical system, to enhance underwater mapping and blue carbon inventory, providing valuable information for environmental monitoring and conservation efforts. By generating and analysing side-scan sonar maps in real time, the robot can interpret the underwater environment as it explores the seafloor and autonomously adapt its mission based on the information it acquires, improving the efficiency and quality of underwater inspection and mapping operations.

The work was presented by Dr. Nuno Gracias, together with PhD candidates Hayat Rajani and Valerio Franchi from CIRS. The poster introduce the first underwater stereo event-camera setup developed within the project. The system uses an AMD Kria KV260 to preprocess the large volume of event data before feeding it to a SpiNNode neuromorphic board, built around the SpiNNaker2 chip, which runs spiking neural networks for classification. The high temporal resolution and high dynamic range of event cameras cope with the rapid motion and uneven illumination underwater, while their low power consumption supports the long survey missions that broad blue carbon inventory requires.

Valerio and Hayat also took the opportunity to present ongoing work from two other projects. One of the posters introduced a multi-robot system for total body photography at dermatoscopic image quality, a line of research begun under the iToBoS project and continued since its conclusion. The work-in-progress framework uses four UR10 manipulators with end-effector cameras, combining view planning and multi-robot scheduling with a real-time mole tracker in a visual servoing loop, allowing it to adapt to individual patient anatomies and capture consistent high-resolution images while reducing examination time and operator dependency. The other poster reported preliminary results from the ongoing tech transfer project OculaRobot an autonomous framework for precision intravitreal injection, one of the highest-volume medical procedures worldwide. The system pairs a 6-DOF collaborative manipulator with a trifocal stereoscopic vision rig for real-time 3D tracking of the eye and needle, using visual servoing and force feedback to target sub-millimetre positioning accuracy. Both posters were presented at the well-regarded workshop on robot-assisted medical imaging, RAMI .

Additionally, Hayat presented a poster from the work carried out at Heriot-Watt University, introducing a controlled benchmark designed to systematically evaluate modern 3D reconstruction methods under variations in medium and lighting. The benchmark comprises 13 datasets spanning two media (air and water) and three lighting conditions (ambient, artificial, and mixed), with additional variations in motion type, scanning pattern, and initialization trajectory, resulting in a diverse set of sequences.

Funded by the Agencia Estatal de Investigación (AEI) and the NextGenerationEU programme, the IURBI project is now entering its final stage. The technologies developed within the project contribute to the advancement of more intelligent and autonomous underwater robotic systems, with potential applications in marine exploration, environmental monitoring and the conservation of marine ecosystems, reinforcing the role of technological innovation in addressing scientific and societal challenges.

The post ViCOROB presents latest IURBI advances and research innovations at ICRA 2026 appeared first on Vicorob.

As part of the conference programme, the presentation entitled “DIVE INTO LEARNING Project: Inclusive STEAM Education with Low-Cost Underwater Robots” was delivered to showcase this Erasmus+ project, which aims to promote more inclusive STEAM education through the use of low-cost underwater robots and project-based learning methodologies.

The project seeks to foster social inclusion, support teachers, and enhance the participation of students from underrepresented and minority groups through innovative educational activities. Within this framework, DIVE Into Learning is developing a curriculum based on underwater robotics and marine sciences to bring technology and research into new educational contexts while ensuring that all learners can successfully acquire knowledge and skills in these disciplines.

Participation in CUIEET, a conference that brings together engineering schools from across Spain, provided an opportunity to increase the project’s visibility at the national level and to share this educational approach with the academic community interested in educational innovation and inclusive STEAM methodologies.

The post Vicorob presents the DIVE Into Learning project at “Congreso Universitario de Innovación Educativa en las Enseñanzas Técnicas” appeared first on Vicorob.

La sessió va apropar al públic alguns dels avenços més recents en l’estudi del cervell humà i el paper que hi juga actualment la intel·ligència artificial. Durant la conferència, Casamitjana va explicar com les noves eines computacionals permeten connectar diferents nivells d’estudi del cervell, des de l’escala microscòpica de les cèl·lules fins a l’anàlisi macroscòpica dels sistemes cerebrals i la seva interrelació.

La conferència també va presentar el projecte NextBrain, una iniciativa de recerca que utilitza tècniques d’intel·ligència artificial per oferir un mapa complet de l’arquitectura cel·lular del cervell sense precedents. Les tècniques desenvolupades permeten una anàlisi ràpida, precisa i accessible d’imatges cerebrals en individus vius. Aquest enfoc permet identificar patrons cerebrals complexos, facilitant l’estudi del desenvolupament i l’envelliment cerebral, així com en l’impacte de diverses malalties neurodegeneratives. Totes les eines del projecte NextBrain han estat publicades lliurement a la comunitat científica per a futurs estudis: https://github-pages.ucl.ac.uk/NextBrain

Veiem, doncs, com la intel·ligència artificial esdevé una tecnologia crucial en l’estudi del cervell, ja que permet examinar grans quantitats de dades amb patrons complexes. Obre les portes a estudis fins ara inimaginables, integrant dades de múltiples fonts que anticipin la detecció de malalties cerebrals. Ens permetrà, per exemple, poder dissenyar protocols i intervencions personalitzades i, fins i tot, crear bessons digitals que permetin simular la evolució dels pacients i l’impacte dels tractaments.

El cicle “Últimes fronteres. La ciència al segle XXI”, organitzat per la Casa de Cultura de Girona, té com a objectiu apropar la recerca científica i tecnològica més actual a la ciutadania. La sessió es va gravar en vídeo i estarà disponible al canal de Youtube de la Casa de Cultura de Girona.

The post La recerca en IA aplicada al cervell humà centra una conferència d’Adrià Casamitjana appeared first on Vicorob.

The applications presented span high-impact domains such as ecology (biodiversity estimation, tree species census, and biomass assessment) and cultural heritage preservation through the development of large-scale databases of historical documents.

The visit also included working meetings with the obstetrics team at Dr. Josep Trueta University Hospital, involving Dr. Anna Maroto and Dr. Clara Martínez, to explore ongoing research lines in fetal ultrasound imaging and identify new opportunities for clinical collaboration.

This activity is part of a long-standing collaboration between the two researchers, initiated in 2019 and consolidated through joint publications and competitive research proposals. In this context, it is also framed within the Ramón y Cajal programme awarded to Mariano Cabezas (RYC2023-042706-I), one of Spain’s flagship initiatives for the recruitment and consolidation of research talent, which supports his upcoming research stay in Japan and enables the expansion of these joint research lines. In parallel, Yago Díez’s involvement is linked to the J-PEAKS programme (2026 J-PEAKS Accelerated International Network Construction Support Program), aimed at fostering international research networks.

The post International collaboration in Computer Vision, Deep Learning and Medical Imaging appeared first on Vicorob.

A Day of Collaboration and Learning

The day was thoughtfully structured to combine strategic planning with practical experience:

In the morning, partners gathered at UdiGitalEdu, the research group of the University of Girona coordinating the project, to:

• Establish project protocols ensuring smooth coordination and collaboration
• Plan dissemination activities to raise awareness and engage target groups, focusing on secondary multicultural schools
• Co-design tools for collecting data to perform a thorough current situation analysis, ensuring that project resources are based on solid evidence and informed decisions

In the afternoon, the group moved to the CIRS (Underwater Vision and Robotics Research Centre), where partners:

• Participated in capacity-building workshops on low-cost underwater robotics
• Explored innovative STEAM teaching methodologies and practical applications for marine science and technology education
• Shared knowledge and experiences regarding inclusive education principles and culturally responsive teaching, ensuring the DIVE outputs meet the needs of diverse student populations

Looking Ahead: Transforming STEM Education

Over the next three years, DIVE will:

• Develop an inclusive hands-on curriculum in the fields related to underwater robotics and marine science
• Train 260 teachers in innovative, interdisciplinary STEAM approaches
• Reach 4,000 students in multicultural classrooms
• Build a sustainable network of educators across Spain (Catalonia and Canary Islands), Greece, and Portugal to foster collaboration and knowledge exchange

The Girona kick-off provided a dynamic space for partners to connect, share expertise, and lay the groundwork for the project’s objectives.

Stay tuned as we dive into this exciting journey, shaping the future of STEAM education across Europe!

The post DIVE into Learning Kicks Off with First Transnational Meeting in Girona appeared first on Vicorob.

During the conference, Vicorob presented the poster “Volumetric-Guided Brain Image Synthesis with Diffusion Models”, showcasing a novel approach to generating and transforming brain MRI images using artificial intelligence.

The work introduced a method that can generate brain MRI images and transform existing ones. It allows adjusting specific brain regions to explore “what if” scenarios, such as simulating changes related to aging or neurological conditions, and can predict how brain structure may evolve over time. These capabilities provide a flexible tool for studying brain changes and supporting research in neuroscience and medical imaging.

The conference program included keynote talks by leading researchers such as Ellen Van Obberghen-Schilling, who presented advances in AI-driven spatial imaging for personalized tumor treatments; Tom Vercauteren, who explored AI-powered hyperspectral imaging for real-time surgical support; and Katrien Verbert, who discussed interactive and conversational AI to improve the understanding of AI-based decisions.

Vicorob’s participation in IABM 2026 reinforces its commitment to advancing artificial intelligence technologies with a strong focus on real-world biomedical applications and societal impact.

The post Vicorob presents new AI-based approach for brain image simulation at IABM 2026 appeared first on Vicorob.

The workshop brought together all the research teams whose projects were selected in this call, focusing on robotics and digital technologies for sustainable agriculture. MULTIFUSE, a project with participation from Vicorob, is one of the six funded projects addressing how robotics and digital technologies can support more sustainable agricultural practices.

This first meeting provided a valuable opportunity to network with other international teams, exchange perspectives, and start shaping collaboration between European and Japanese partners.

Robotics and digital technologies for sustainable agriculture

On January 31, 2025, the EIG CONCERT-Japan initiative announced the six selected projects of its 11th joint call on digital transformations and robotics in sustainable agriculture.

MULTIFUSE: artificial intelligence for plant stress detection

The MULTIFUSE project focuses on advanced multimodal sensing and data fusion for early digital detection of plant stress symptoms.

By combining data from various optical sensors, the research trains artificial intelligence to detect plant stress, such as water deficiency or infection, at a physiological level before it becomes visible to the human eye.

Other projects in robotics and agriculture

The six selected projects address sustainable agriculture through robotics, artificial intelligence, and digital technologies:

• HydroNPK-AI focuses on AI-enhanced NPK management for optimized hydroponic cultivation. Using real-time artificial intelligence, the system manages nitrogen, phosphorus, and potassium in hydroponic setups to maximize yield while reducing chemical runoff.
• DRAGONS develops drones equipped with robotic arms to autonomously collect plant samples such as leaves or fruit from complex vineyard canopies.
• DEMETER builds adaptive pruning robots through simulation, artificial intelligence, and intuitive teleoperation, allowing human experts to remotely guide robotic systems.
• DYNA-GROW focuses on dynamic lighting management systems and sustainable energy solutions for smart crop production, integrating renewable energy with intelligent lighting.
• Supporting Digital Solutions develops a framework to support the demonstration of sustainable digital solutions for agriculture and enable collaboration between Japanese and European startups.

Social sustainability in agriculture

In both Japan and Europe, the average farmer is over 60 years old. These projects aim to make agriculture physically easier and more attractive to younger generations through robotics and digital technologies.

International collaboration in robotics and sustainable agriculture

The workshop in Bonn marked the beginning of collaboration between the selected teams, enabling them to connect, exchange perspectives, and start working together in the field of robotics and sustainable agriculture.

Vicorob’s participation in MULTIFUSE is part of this international effort to explore how robotics and digital technologies can support more sustainable agricultural practices.

The post Vicorob participates in EIG CONCERT-Japan workshop on robotics and sustainable agriculture appeared first on Vicorob.

Prof. Pere Ridao, Director of CIRS, and Dr. Roger Pi Roig are representing the team during the event.

Their participation is linked to the MEMLS laser project, supported by the AGAUR Producte programme. The project focuses on advancing underwater 3D laser scanning technologies aimed at improving high-resolution seabed mapping and inspection capabilities.

More information about the project can be found here.

The Vicorob team engaged with IQUA Robotics, a spin-off closely linked to the institute.

The post Vicorob researchers attend Oceanology International to showcase MEMLS laser project appeared first on Vicorob.

Abstract:

This PhD thesis focuses on the development of deep learning methods to enhance medical image analysis, with a particular emphasis on improving focus, efficiency and fairness in acute ischemic stroke (AIS). AIS is a cerebrovascular disease that occurs when a cerebral artery becomes occluded, interrupting blood flow to part of the brain. Rapid diagnosis and treatment of AIS are essential to preserving salvageable tissue and minimizing long-term disability. However, not all patients benefit equally from current therapies despite similar clinical and procedural characteristics. Accurately identifying patients likely to benefit remains a major clinical challenge. In this context, neuroimaging, particularly brain Computed Tomography Angiography (CTA), plays a central role in patient triage during the acute stroke phase. The rich anatomical and vascular information present in CTA offers a valuable but complex input for automated image analysis, motivating the use of deep learning to support clinical decision-making.

This thesis explores strategies to fully utilize CTA data using deep learning methods tailored for AIS. The first contribution proposes strategies to guide neural networks toward vascular structures extracted from CTA while retaining contextual parenchymal information. Several methods to combine vascular segmentations and CTA data are evaluated, including an attention-inspired mechanism designed to enhance the model’s focus on clinically relevant features for AIS due to large vessel occlusion (LVO) detection. The second contribution introduces Learnable 3D Pooling (L3P), a novel convolutional neural network-based module that compresses
3D medical images into 2D feature maps, enabling efficient, lightweight, and interpretable models. L3P-based architectures are validated across multiple tasks, including LVO detection in CTA, as well as brain age prediction from 3D T1-weighted MRI. In all cases, L3P maintains competitive performance compared to fully 3D networks, while significantly reducing computational demands and enhancing feature interpretability. The third contribution addresses the issue of hidden confounders in medical imaging pipelines. A controlled experimental framework is proposed to simulate and analyze the effects of confounding variables in clinically relevant classification tasks. Using large ensembles of bootstrapped models, measurable distributional patterns, such as inflated model performance, reduced performance variability and convergence of training and validation metrics, are identified as indicators of confounder-driven learning. This enables the development of a practical, unsupervised method to flag potential hidden biases, even when the nature of the confounder is unknown.

The proposed approaches are broadly applicable across medical imaging modalities and disease domains, with particular relevance to neuroimaging. Designed with generalizability in mind, these methods have demonstrated utility beyond stroke, highlighting their potential for diverse clinical contexts. Collectively, the contributions of this thesis advance the development of deep learning tools with efficiency, focus, and fairness.

The complete doctoral thesis can be consulted in the official PhD repository of the University of Girona (DUGi-doc):  https://dugi-doc.udg.edu

The post Doctoral Thesis: Deep Learning for Stroke Imaging: Enhancing Focus, Efficiency, and Fairness appeared first on Vicorob.

Over 30 teachers from Spain, Italy, Romania, Bulgaria, Ireland, and Greece came together to explore how Montessori-inspired methods and creative technologies can change how mathematics is taught and learned in primary and lower secondary schools, especially in multicultural classrooms.

Over three inspiring days, participants:

• Explored the first version of the MARIAN Lesson Plan Collection
• Tried out classroom activities with children and saw how hands-on and technology-based learning can help students understand mathematics better
• Discussed the benefits of using active, inclusive, and creative methods in teaching mathematics

After these first training sessions, participants will try different activities in their classrooms and share their experiences. Their feedback will help the consortium create the second version of the MARIAN Lesson Plan Collection, which will be discussed at a meeting in Sofia.

Next, participants will become teacher trainers, sharing the MARIAN approach by leading workshops in their own countries. They will also help update the MARIAN Lesson Plan Collection in several languages. The project’s goal is to introduce new, inclusive, and engaging ways of teaching mathematics in classrooms across Europe.

The post Re-imagining Maths: MARIAN Training of Trainers in Girona appeared first on Vicorob.