Europe launches VICTOR-XR to make virtual worlds safer, smarter and connected to reality

A new Horizon Europe project brings together 16 organizations to transform manufacturing, human-robot collaboration and rehabilitation through next-generation Extended Reality

Universitat Jaume I

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Virtual worlds are rapidly moving beyond gaming and entertainment into factories, hospitals and training environments. Yet one major challenge remains: ensuring that what happens in a virtual environment accurately reflects what is happening in the real world.

To address this challenge, the European research initiative VICTOR-XR, launched under Horizon Europe’s Cluster 4 – Digital, Industry and Space, within the HORIZON-CL4-2025-03-HUMAN-14 topic, brings together 16 partners from seven countries to develop a new generation of intelligent, human-centric Extended Reality (XR) technologies.

Over the next three years, VICTOR-XR will create technologies that continuously synchronise physical environments with their virtual counterparts using Digital Twins, multimodal sensing, and AI-powered cognitive assistants. By combining vision, speech, gaze tracking, biosignals and haptic feedback, the project aims to deliver immersive experiences that are more realistic, more responsive and ultimately more trustworthy.

At the heart of the project is a new concept known as Virtual-Physical Consistency, a framework designed to ensure that virtual worlds remain accurately aligned with real-world processes, people and environments in real time. The technology will enable systems to identify discrepancies, understand user actions and provide intelligent assistance through adaptive XR interfaces and AI co-pilots.

Rather than developing technology in isolation, VICTOR-XR will validate its innovations in three large-scale pilot environments where accuracy, safety and human performance are critical.

In the automotive sector, VICTOR-XR will help engineers and operators interact with digital twins of products and production processes before physical prototypes exist. By identifying potential assembly and design issues earlier, manufacturers can reduce errors, shorten validation cycles and improve productivity while creating new immersive training opportunities for workers.

In advanced manufacturing environments, workers increasingly collaborate with robots. VICTOR-XR will create XR interfaces that visualise robot intentions, monitor operator actions, and deliver adaptive guidance in real time. The goal is to improve productivity while increasing safety, trust and ergonomics within collaborative workspaces.

In healthcare, the project will support rehabilitation programmes for people with chronic musculoskeletal conditions. Through immersive XR experiences, digital twins and empathetic AI co-pilots, patients will receive personalised guidance and feedback, while clinicians gain new tools to monitor progress and adapt therapies remotely.

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Credit: VICTOR-XR

Virtual worlds are rapidly moving beyond gaming and entertainment into factories, hospitals and training environments. Yet one major challenge remains: ensuring that what happens in a virtual environment accurately reflects what is happening in the real world.

To address this challenge, the European research initiative VICTOR-XR, launched under Horizon Europe’s Cluster 4 – Digital, Industry and Space, within the HORIZON-CL4-2025-03-HUMAN-14 topic, brings together 16 partners from seven countries to develop a new generation of intelligent, human-centric Extended Reality (XR) technologies.

Over the next three years, VICTOR-XR will create technologies that continuously synchronise physical environments with their virtual counterparts using Digital Twins, multimodal sensing, and AI-powered cognitive assistants. By combining vision, speech, gaze tracking, biosignals and haptic feedback, the project aims to deliver immersive experiences that are more realistic, more responsive and ultimately more trustworthy.

At the heart of the project is a new concept known as Virtual-Physical Consistency, a framework designed to ensure that virtual worlds remain accurately aligned with real-world processes, people and environments in real time. The technology will enable systems to identify discrepancies, understand user actions and provide intelligent assistance through adaptive XR interfaces and AI co-pilots.

Rather than developing technology in isolation, VICTOR-XR will validate its innovations in three large-scale pilot environments where accuracy, safety and human performance are critical.

In the automotive sector, VICTOR-XR will help engineers and operators interact with digital twins of products and production processes before physical prototypes exist. By identifying potential assembly and design issues earlier, manufacturers can reduce errors, shorten validation cycles and improve productivity while creating new immersive training opportunities for workers.

In advanced manufacturing environments, workers increasingly collaborate with robots. VICTOR-XR will create XR interfaces that visualise robot intentions, monitor operator actions, and deliver adaptive guidance in real time. The goal is to improve productivity while increasing safety, trust and ergonomics within collaborative workspaces.

In healthcare, the project will support rehabilitation programmes for people with chronic musculoskeletal conditions. Through immersive XR experiences, digital twins and empathetic AI co-pilots, patients will receive personalised guidance and feedback, while clinicians gain new tools to monitor progress and adapt therapies remotely.

Human-centred technology by design

As AI and virtual worlds become increasingly integrated into everyday life, VICTOR-XR places ethics, transparency and inclusion at the centre of its approach. Privacy, accessibility, explainability and compliance with European regulatory frameworks will be embedded across all developments, ensuring that technological innovation remains aligned with European values.

The project also aims to support Europe’s strategic ambitions in Virtual Worlds and Industry 5.0 by contributing to standards development, promoting interoperability and creating new XR-based learning and training pathways that can accelerate adoption across sectors.

“Virtual worlds can only become truly useful when they remain connected to reality. Through VICTOR-XR, we are building technologies that help people, machines and digital systems work together more effectively, safely and intelligently.”

By combining artificial intelligence, digital twins, and immersive technologies, VICTOR-XR aims to show how virtual worlds can create measurable benefits for industry, healthcare professionals, and citizens alike, paving the way for a more human-centric digital future for Europe.

More information

Website: victorxr.eu

LinkedIn: linkedin.com/company/135256989/

YouTube: https://www.youtube.com/@VICTOR-XR-project 

 

Television gains ground in streaming platform era, study shows

Research published in Communication & Society finds that video-on-demand services are not replacing traditional television for series viewing in Spain

University of Alicante

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The UA study analysed 325 fiction series released in Spain between 2020 and 2024.

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Credit: University of Alicante

A University of Alicante (UA) study of 325 fiction series released in Spain between 2020 and 2024 has concluded that video-on-demand (VOD) platforms have not replaced traditional television. Instead, the two distribution models are developing new ways of collaborating and sharing content.

That is one of the main findings of the research, published in Communication & Society. The study examines the relationship between linear television and the eight leading digital platforms operating in Spain, showing that, far from displacing one another, the two systems are settling into models of coexistence, joint ventures and content circulation.

The research, titled ‘From prime time to binge-watching: Launch strategies and collaboration between TV and VOD in Spain (2020–2024)’, was carried out by doctoral researcher Jorge Abad and Dr Tatiana Hidalgo, a lecturer in the UA’s Department of Communication and Social Psychology.

The authors assessed 325 serialised fiction titles, comprising 191 series, 51 miniseries and 83 documentary series. Of these, 222 were released in full on a single date, 102 followed a weekly schedule and two used a hybrid model.

Viewers favour weekly releases

The study confirms that, while releasing full seasons at once remains the main strategy for streaming platforms, weekly releases still carry considerable weight. Netflix, for instance, concentrates on full-season releases, whereas Movistar+ is moving towards greater use of weekly episodes. Prime Video, HBO Max and Disney+ take a flexible approach, while Atresplayer stands out for its commitment to one episode a week.

Notably, weekly releases achieved an average rating of 6.8 on IMDb and Filmaffinity, compared with 6.6 for full-season releases. The authors noted that episodic releases foster stronger emotional engagement among viewers and enhance perceived narrative quality.

The article also highlights growing collaboration between television and VOD platforms, identifying more than 40 seasons tied to joint production models. As Abad and Dr Hidalgo explain, co-productions and distribution agreements allow organisations to share costs, spread risk and extend the commercial life of their productions.

The researchers stressed that television remains essential for building visibility. Although streaming platforms have transformed how audiences consume media, the findings indicate that linear television retains a key role as the main window for visibility, credibility and creating a sense of event around a series.

In this context, when a production later moves to a VOD platform, the streaming service can prolong its shelf life, introduce it to new audiences and widen its distribution. The reverse journey, however, from platform to linear television, does not guarantee the same impact on broadcast TV.

Looking ahead, the article points to a balance between the two models in the Spanish media landscape. Platforms retain distinct brand identities but are adopting increasingly flexible and collaborative strategies to optimise a title’s lifecycle across broadcast television and VOD, the authors added.

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Journal

Communication & Society

DOI

10.15581/003.39.2.010

Method of Research

Data/statistical analysis

Subject of Research

Not applicable

Article Title

“From prime time to binge-watching: Launch strategies and collaboration between TV and VOD in Spain (2020-2024)”

 

The missing link between event cameras and robot vision

Penn's Fast Feature Field could make ultrafast, eye-inspired cameras as practical for robots as conventional cameras.

University of Pennsylvania School of Engineering and Applied Science

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A drone equipped with an event camera, which allows it to see in a manner similar to biological eyes.

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Credit: Sylvia Zhang, Penn Engineering

For decades, event cameras, which emulate the biological retina by continuously monitoring changes in light intensity, have promised to revolutionize how robots perceive the world by allowing them to react faster and operate more reliably than conventional cameras permit. 

But interpreting event-camera data, which resembles a dizzying stream of points rather than a recognizable series of images, has traditionally required a patchwork of specialized algorithms, each built for a single task.

Now, engineers at the University of Pennsylvania have developed Fast Feature Field, or F3, a general-purpose computational tool to efficiently transform the tens of millions of signals that event cameras produce each second into information that many different kinds of robots can use.

The tool could transform robotics by allowing for the widespread use of event cameras in platforms like self-driving cars and drones for the first time, improving robots’ ability to recognize objects, estimate distances and perceive motion in many different lighting conditions.

“We expect this to be a watershed moment in the history of event cameras, showing how to make event-camera processing reliable, fast and broadly useful,” says Pratik Chaudhari, Associate Professor in Electrical and Systems Engineering (ESE) with a secondary appointment in Computer and Information Science (CIS) and senior author of a new paper in Science Robotics. “Fast Feature Field could make the robots that increasingly fill our skies and streets much safer by helping them see the world more accurately.”

Cameras Like Eyeballs

Unlike conventional cameras, which record complete images at regular intervals (i.e., 30 frames per second), event cameras continuously respond to incoming light. “Event cameras are like the rods and cones in the mammalian retina,” says Kostas Daniilidis, Ruth Yalom Stone Professor in CIS and a co-author of the paper. “They detect changes in light, and can tell you when certain regions got brighter or darker.”

But unlike biological eyes, which have additional layers of cells to interpret that information, event cameras have never had a general way to extract meaningful patterns from their own data. “The retina has many cells beyond rods and cones,” adds Richeek Das, a doctoral student in CIS and the paper’s first author. “Ganglion cells detect motion and color, for instance, while structures like amacrine cells help suppress redundant information.” 

The lack of software to take the place of that additional processing has been a central hurdle to event cameras catching on beyond limited research applications. “Without the ability to remove redundant information,” says Chaudhari, “the data from an event camera is far too noisy and voluminous to use directly.”

Predicting the Future

The researchers initially tried to solve the problem by using mathematical techniques for summarizing visual information, and sought to develop the equivalent of the Fast Fourier Transform, a widely used tool in signal processing for breaking complex signals into their component parts, for event cameras. 

But after months of experimentation, the team struggled to find an approach that could reliably start from the vast information rate of an event camera and end by capturing the layout of a scene and motion within it.

Eventually, the researchers realized that they could train a neural network, a form of AI that learns from data, to discover its own way of summarizing the signals. The question was how to teach it which patterns to recognize.

The answer, they found, was prediction. “To accurately anticipate future events based on past ones, the network must learn to represent both the structure of a scene and the motion taking place within it,” says Das. “By training F3 to predict future events, we could teach it to identify the underlying patterns in the data without designing a separate approach for every task.”

Skipping the Empty Space

The result was a general-purpose way to represent event-camera data. But turning that insight into software fast enough for robots to use presented another challenge. “Our initial implementation was too slow for the rapid, real-time perception that makes event cameras so appealing,” says Chaudhari.

The solution came from recognizing that most of the possible positions where an event could occur were actually empty. “Even though an event camera can produce tens of millions of signals per second, roughly 95% of the possible positions in the data contain no events at all,” says Das. 

In other words, most of the camera's pixels have nothing new to report at any given moment. “We realized we could perform calculations only where events actually occur,” adds Das, “rather than processing all that empty space.”

A Common Language for Event Cameras

Earlier this year, Sony AI unveiled Ace, a ping-pong-playing robot that uses event cameras to track the speed and spin of a ball, allowing it to compete with and defeat professional players. 

However, Ace's sophisticated vision system was developed specifically for table tennis, illustrating a longstanding obstacle to the wider adoption of event cameras: Engineers have traditionally had to develop specialized software for each new application, rather than relying on existing computer-vision tools.

“Just as compression formats like JPEG and MPEG made it easier to share pictures and videos across different devices,” says Daniilidis, “F3 gives event cameras a common language, transforming their signals into a format that the enormous range of software already developed for conventional cameras can be adapted to use.”

Fast, Flexible Robot Vision

To demonstrate that versatility, the researchers tested F3 on tasks ranging from recognizing objects to estimating distances and tracking motion, using data collected from cars, four-legged robots and flying drones, all in environments that varied from urban streets at night to crowded indoor spaces.

The results combined accuracy with speed: F3-based approaches achieved state-of-the-art performance on multiple robotic perception tasks. Algorithms using F3 were roughly two to five times faster than previous approaches, and F3 itself processed high-definition event-camera data 120 times per second, or 440 times per second at lower Video Graphics Array (VGA) resolution. “F3 can enable real-time event-based perception for many different kinds of robots,” says Das. 

In ongoing work with Dexter Ong and Ioannis Asmanis, both doctoral students in CIS, the team is using F3 to build autonomous drones that can navigate cluttered and poorly lit environments using event cameras. “It opens up exciting possibilities for agile drones,” says Daniilidis. “F3 has become a key component of our pipeline.”

The Future of Event Cameras

Eventually, the researchers envision baking F3 directly into the circuitry of event cameras, where it could function like an efficient camera driver, automatically transforming raw signals into a format that existing computer-vision software can readily use.

“Our goal is to make using an event camera as straightforward as using a conventional one,” says Chaudhari. “We want engineers to be able to take advantage of these cameras' extraordinary capabilities without having to reinvent the software every time they want a robot to do something new.”

This study was conducted at the University of Pennsylvania School of Engineering and Applied Science. This project was funded in part by the National Science Foundation (IIS-2145164, CCF-2212519) and the Internet of Things for Agriculture Engineering Research Center (NSF Grant EEC-1941529). 

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Journal

Science Robotics

DOI

10.1126/scirobotics.aec8218

Method of Research

Computational simulation/modeling

Subject of Research

Not applicable

Article Title

Fast Feature Field (F3): A general predictive representation of events for robot perception

Article Publication Date

24-Oct-2026

From left: Dexter Ong, Richeek Das, Kostas Daniilidis, Ioannis Asmanis and Pratik Chaudhari, with a drone equipped with an event camera, center.

Credit

Sylvia Zhang, Penn Engineering

What an Event Camera Sees [VIDEO] 1

What an Event Camera Sees [VIDEO] 2

What an Event Camera Sees [VIDEO] 3

F3 translates the continuous stream of data from an event camera into information that existing computer vision software can use, drastically expanding the possibilities for using event cameras in robots today. 

Credit

Richeek Das, Kostas Daniilidis, Pratik Chaudhari, Penn Engineering

 

Record-setting 2.75 gigahertz LED designed for fast, energy-efficient data centers

University of Illinois Grainger College of Engineering

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World-record micro-LED with 2.75 gigahertz optical modulation bandwidth.

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Credit: The Grainger College of Engineering at the University of Illinois Urbana-Champaign

A collaboration between the University of Illinois Urbana-Champaign’s Grainger College of Engineering and the University of Notre Dame has broken the world record for optical switching speed in quantum well LEDs. The gallium nitride micro-LED device has an optical modulation bandwidth of 2.75 gigahertz while consuming just 25 milliwatts of power. Its design was optimized to bring newfound speed and efficiency to communication links in data centers.

As the team of researchers reports in IEEE Electron Device Letters, this achievement is the result of an extensive program of theoretical modeling and empirical testing, providing a roadmap to scaling down LED devices for optical communications. For the record-breaking device, the design was optimized to a size of 5 micrometers. The team hopes that their design will prove to be a vast improvement in speed and efficiency over conventional wire interconnects and even laser-based optical links for short-range communication.

“Ninety percent of communications in data centers is short range, meaning less than 10 meters,” said Illinois Grainger Engineering graduate student Abdelghany Abouelnagga, the study’s lead author. “It is standard to use lasers for the kind of high-frequency communications needed in this context, but lasers are power hogs. If we want to manage energy use in data centers, we need to consider lower-power optical communications such as LEDs, and we show exactly how to do so.”

This study was conducted by the research groups of Illinois Grainger Engineering electrical and computer engineering professors Can Bayram, Peter Dragic and Milton Feng; and Notre Dame electrical engineering professor Patrick Fay.

To increase the speed with which data centers operate, it has been necessary to use optical communication links that transmit information using light pulses. Unlike copper wires, optical links can transmit at very high rates, or frequencies, without experiencing significant loss. It is necessary to use a tightly controlled light source to achieve high frequencies without sacrificing accuracy.

Until now, that has meant using lasers, but they require large amounts of power and generate large amounts of heat. The alternative is to use another tightly controlled light source such as LEDs. To create a device that is not only fast but optimized for use in data centers, the researchers systematically studied how the optical modulation bandwidth — a measure of how fast the micro-LED can switch on and off before the light loses brightness — and power consumption vary with device size.

“We systematically shrunk our micro-LEDs down from 100 micrometers to 2 micrometers in diameter, a level of deep scaling that has never been done before,” Abouelnagga said. “We found that, contrary to popular belief, smaller is not always better. Our work gives a development roadmap to systematically study the tradeoffs between size, bandwidth and power consumption, which shows that the best device is actually the 5-micrometer one.”

To fabricate their optimized micro-LED devices, the researchers needed to have a precise understanding of the material imperfections leading to so-called parasitic effects in device performance. Abouelnagga recalls that it was necessary to model the materials and electrical properties in detail beforehand to ensure an optimal design.

The device’s performance is a record for quantum well LEDs, the industry standard design. Certain nonstandard LED designs can operate at higher frequencies, but such designs create unstable, low-intensity light. The researchers believe their 5-micrometer quantum well design is much better suited to data center usage not only for its optical power and bandwidth, but for its extraordinarily low energy consumption and material platform scalability.

“To put the speed and power efficiency in perspective, our micro-LED responds to electrical signals on a gigahertz scale, comparable to computer processors, but consumes just 25 milliwatts of electrical power,” Abouelnagga said. “Of course, processors and optical transmitters perform different functions, but the comparison illustrates how fast this tiny light source can respond with a small power budget. Its 5-micrometer diameter also opens the possibility of arranging many emitters into compact, two-dimensional arrays with each carrying a separate stream of data.”

Zetai Liu and Jonathan Wright also contributed to this study.

The article, “Scaling of GaN Micro-LEDs with a 2.75 GHz Bandwidth for High-Speed Optical Links,” is available online. DOI: 10.1109/LED.2026.3745737

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Illinois Grainger Engineering Affiliations

Can Bayram is an Illinois Grainger Engineering professor of electrical and computer engineering in the Department of Electrical and Computer Engineering. He is a resident faculty member in the Holonyak Micro and Nanotechnology Laboratory. He holds an Intel Alumni Endowed Faculty Scholar appointment.

Peter Dragic is an Illinois Grainger Engineering associate professor of electrical and computer engineering in the Department of Electrical and Computer Engineering. He is a resident faculty member in the Holonyak Micro and Nanotechnology Laboratory.

Milton Feng is an Illinois Grainger Engineering Professor Emeritus of electrical and computer engineering in the Department of Electrical and Computer Engineering. He is affiliated with the Coordinated Science Laboratory and the Holonyak Micro and Nanotechnology Laboratory. He holds a Nick Holonyak, Jr. Endowed Chair Emeritus appointment.

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Journal

IEEE Electron Device Letters

DOI

10.1109/LED.2026.3745737

Article Title

Scaling of GaN Micro-LEDs with a 2.75 GHz Bandwidth for High-Speed Optical Links

Article Publication Date

21-Oct-2026