Objectives: To investigate collaborative dynamic robot systems that, unlike classical industrial robots, can operate in unstructured, fully dynamic and partially observable environments, enabling a new range of disruptive services and functionalities for semi-autonomous and autonomous inspection in heterogeneous environments (terrestrial and aquatic).

Research immersive environments for industrial inspection in unattended facilities (renewable energy generation plants, electrical substations, chemical treatment plants), and specifically in sectors that represent risks and complex and high-cost inspections (economic, personnel, time), facilitating the transformation and digitization of strategic sectors in Spanish industry.

Research into new sensory technologies for inclusion in robot-robot and human-robot ecosystems with advanced perception capabilities (immersive and haptic technologies, AI, environmental reconstruction, sensory capabilities, communications architectures) in order to increase and extend human inspection capabilities and promote equipment failure prediction systems, decision support, the sustainability of inspection operations, the efficient use of industrial resources, and efficiency throughout the value chain.

Research on efficient robotic inspection systems (mission resolution, task planning) that facilitate operating cost reduction for industrial plants so that they can operate unattended, promoting energy efficiency and sustainability.

Objectives: The SAVIA URBANA project’s objective is to develop and implement an Analysis and Surveillance System for Urban Areas by creating a cloud platform or standalone server service. This system will allow state security forces and agencies (FFCCSE for its Spanish acronym) to operate in urban centers through the application of analysis techniques based on Machine Learning, Deep Learning, and Convolutional Neural Networks. The platform will carry out the analysis and interpretation of as any source of images or other data from sensors installed in the field and compiled in urban areas. Furthermore, this information will be added to the data stored on internal databases belonging to the FFCCSE or any other external public source, including social media.

Objectives: The project’s general objective is to develop a cloud platform that makes it possible to automatically detect and inventory vehicle damages after an accident by applying Convolutional Neural Networks to video images that any user can take with a camera or phone. The platform will also display all of the damages on a 3D model of the vehicles in the platform’s viewer, where the user will be able to see each part of the vehicle that has been affected (doors, headlights, fenders, etc.), the size or extent of the damage, the video frames that show the impact, the monetary assessment of the damages, and the best option for the repair or substitution of the affected parts, minimizing appraisal and repair costs.

Objectives: The project’s objective is to design a complete system to create and manage 3D eCommerce platforms, enabling the next technological leap forward in eCommerce and marketplaces, while at the same time improving connections between sellers and consumers and providing a content generation tool. Sellers will gain a powerful and innovative tool for marketing and sales, while consumers will experience an improved shopping experience.