As part of the ForNeRo research project, Professor Dirk Wilhelm (right) and researcher Luca Wegener (left) are working together. Image courtesy of Astrid Eckert / TUM

How can robots and humans work together as effectively as possible in the operating room of the future? Researchers from the Technical University of Munich (TUM) and TUM University Hospital investigated this question as part of the ForNeRo research project. Using a sensor-equipped system, they analysed surgeons’ movements during procedures and collected data from simulated robot-assisted operations.

Five depth cameras mounted on the ceiling of the experimental operating theatre at TUM University Hospital in Munich generate a three-dimensional digital image of the room 15 times per second –a digital twin of the surgical environment. At the operating table stands Prof. Dirk Wilhelm, Head of the Chair of Medical Robotics at TUM and a surgeon and senior physician at TUM University Hospital. He is wearing a suit fitted with motion markers on the joints and head, tracked by an infrared system with ten cameras. Microphones record and spatially locate conversations within the surgical team, while additional physiological data is collected to measure stress levels among staff.

The aim of this sensor data and the digital twin is to improve surgical workflows, integrate robotic assistance systems into clinical workflows as efficiently and ergonomically as possible, and ultimately reduce the workload of medical staff. The sensor system developed by Prof. Wilhelm’s research group for minimally invasive interdisciplinary therapeutic intervention (MITI) is now being used for the first time in Germany to collect data from a real operating room environment. “In the next step, this data could help improve the use of robots in surgery,” says Prof. Wilhelm. All data collection in the operating room requires the consent of patients and all parties involved.

Testing robotic systems in routine surgical procedures

For robotic systems to assist in future operating rooms, researchers will need more than sensor data alone. The experimental operating theatre therefore serves not only as a data collection platform, but also as a test environment for robot-assisted procedures on anatomical models – in other words, testing collaboration with robotic assistants.

As part of the ForNeRo research project, the researchers investigated three common minimally invasive procedures: gallbladder surgery, inguinal hernia repair, and sigmoid resection, the partial removal of the large intestine. Two robotic systems were used in each procedure. The first, Solo Assist II, held and positioned the endoscope. The second was MIRO, a modular surgical robot developed by the German Aerospace Center (DLR) that surgeons can control using a joystick and other interfaces. During a simulated procedure, the surgeons used MIRO to manipulate a miniature gripper, position a plastic mesh during hernia repair and assist with suturing.

A robot can carry out simple tasks

The simulated operations are designed to help configure robotic systems that can assist surgeons during minimally invasive procedures. To evaluate their potential, Max Bergholz from the Chair of Ergonomics at TUM records surgeons’ postures and movements in a sensor-equipped operating room while performing procedures on anatomical models. Participants are also asked to assess the physical and mental strain experienced during the different phases of the operation.

“Surgeons often report back pain caused by maintaining rigid postures for long periods,” says Bergholz. “Earlier systems also required them to operate as though looking into a mirror, forcing them to constantly adapt their spatial orientation.” His goal is to make surgical work as ergonomic and intuitive as possible.

Robotic systems eliminate much of this need for readjustment. They allow surgeons to operate with greater precision, since larger hand movements with the joystick translate into movements of only a few millimetres inside the body. Unlike established systems like the da Vinci Surgical System, the new system also allows the surgeon to remain physically closer to the patient.

The research showed that robotic assistants can already take over simple tasks in an operating room – such as holding an endoscope – without increasing surgeons’ workload. “This allows us to explore how robotic assistants can be seamlessly integrated into clinical workflows,” says Bergholz.

AI is expected to better understand surgical procedures

Looking ahead, TUM Professor Dirk Wilhelm sees potential for using the complex data from the operating theatre for artificial intelligence applications. “Data are a fundamental building block for AI systems in the operating room,” says Wilhelm. “Such systems could automatically recognize which surgical instruments are being used and identify the organs being operated on.”

The initial goal is to improve surgical workflows and planning processes. In the longer term, AI could help decide when a robotic assistant would be beneficial.

Annual shipments are projected to approach 1.8 million units by 2036, driven primarily by automotive manufacturing, with logistics following and home-use remaining a longer-term opportunity with limited penetration within the forecast period.

This growth is supported by the accelerating push toward Industry 5.0, rapid progress in embodied AI, continuous improvements in materials and component supply chains, and sustained strategic backing from investors and OEMs. Compared with open or highly unstructured environments, industrial settings such as automotive manufacturing offer more standardized workflows, clearer task boundaries, and stronger labour-cost pressure. These conditions make them more likely to become the first scalable deployment markets for humanoid robots.

At the same time, declining hardware costs are reshaping the economic baseline. IDTechEx analysis indicates that the average selling price of humanoid robots is expected to fall from approximately US$114,700 in 2024 to around US$37,000 by 2030, with further reductions expected into the mid-2030s. As capital costs decline, the cost per productive hour falls accordingly, with the most significant reductions occurring during the early stages of commercialization. However, while cost reduction is a necessary condition for adoption, this alone is not a sufficient reason to adopt. The IDTechEx report,”Humanoid Robots: Market, Technologies, and Opportunities 2026-2036″, provides a detailed analysis of humanoid robot market forecasts, cost evolution, ROI scenarios, technology readiness, and key application opportunities.

Comparison with human labour remains scenario-dependent

Based on IDTechEx interviews with major industry participants and amortization calculations across representative commercial deployment scenarios over the next decade, the operating cost of humanoid robots is expected to remain highly dependent on deployment efficiency. Unlike fixed automation systems, humanoid robot utilization can vary significantly by task type, workflow structure, environmental complexity, and system integration level. IDTechEx therefore incorporates multiple utilization scenarios in its modelling to reflect a range of real-world deployment conditions, including high-, medium-, and low-efficiency cases.

IDTechEx’s scenario-based modelling suggests that humanoid robot operating costs could vary significantly depending on deployment efficiency. At the current early-commercialization stage, costs remain highly sensitive to utilization, task continuity, and integration quality. However, as enterprise procurement prices decline and deployment experience improves, high-utilisation industrial scenarios could bring operating costs below US$5/hour by around 2030, with further reductions possible toward 2036.

At face value, this cost level is increasingly attractive when compared with human labour costs. In high-labour-cost markets such as the US, total employer cost is expected to continue rising steadily. In China, labour cost starts from a lower base but grows at a faster rate, reinforcing the long-term economic rationale for automation. However, this comparison needs to be interpreted carefully. A robot’s cost per hour is not directly equivalent to a human labour cost per hour, as it depends on sufficient utilisation, task continuity, and operational stability, all of which remain variable in current deployments.

As a result, humanoid robots are beginning to show cost competitiveness, particularly in high-utilisation industrial scenarios. However, in medium- or low-utilisation settings, the cost advantage can be significantly reduced even as hardware prices fall. In other words, the cost curve is improving, but whether the cost advantage can be realized depends strongly on the deployment environment.

Profitability depends on effective output

From an ROI perspective, IDTechEx calculations suggest that humanoid robots are beginning to show a clear payback pathway under favourable deployment conditions. By 2026, payback periods can be reduced to around 6 months under high-utilisation scenarios, compared with approximately 15 months under medium utilization. As hardware prices continue to decline and deployment experience improves, ROI feasibility is expected to strengthen across a broader range of industrial applications.

However, a shorter payback period should not be interpreted as guaranteed profitability. The core variable in humanoid robot economics is not only equipment cost, but the effective value of the work delivered by the robot. In practical terms, this means whether the robot can perform economically valuable tasks consistently, reliably, and at a sufficient level of productivity across different environments.

This remains the main bottleneck for large-scale adoption. Humanoid robots are becoming increasingly feasible in selected structured industrial environments, but capability limitations remain clear in complex, variable, or safety-critical tasks. In the near term, more realistic deployment pathways are likely to prioritize high-labour-intensity, repetitive, standardized, or hazardous tasks where the economic case is easier to validate.

Overall, IDTechEx believes that the cost advantage of humanoid robots is becoming increasingly visible, and ROI can already be demonstrated in selected deployment scenarios. However, large-scale commercialisation will depend on continued improvements in software capability, task generalisation, system integration, and deployment efficiency, rather than hardware cost decline alone.

The new robot from Prof. Angela Schoellig’s TUM Learning Systems and Robotics Lab looks like a broomstick on wheels with a camera mounted at the top. It is one of the first robots that not only integrates image understanding but also applies it to a clearly defined task.

To find a pair of glasses misplaced in the kitchen, for example, the robot has to look around and build a three-dimensional image of the room. The camera initially provides two-dimensional images, but these pixels also contain depth information. This creates a spatial map of the environment that is accurate to the centimetre and is constantly updated. A laptop also provides the robot with information about which objects are visible in the image and what significance they have for humans.

“We have taught the robot to understand its surroundings,” says Prof. Angela Schoellig. The head of the Robotics Lab at the TUM Chair of Safety, Performance and Reliability for Learning Systems aims to develop robots that can navigate any environment independently. Humanoid robots working in factories or robots in care settings in private homes require this newly developed basic understanding, which, as Schoellig explains, “is important for all robots that move in spaces that are constantly changing”.

Internet knowledge translated into the robot’s language

The robot therefore understands that a table or window sill can be used to briefly set down a pair of glasses, whereas a stovetop or a sink are not suitable for this purpose. “The language model captures the relationships between the objects and we convert this information into the robot’s language,” explains Prof. Schoellig.

Two-digit numbers appear on the three-dimensional map of the environment, constantly recalculating the likelihood that the object being searched for is located there. According to the research results, the robot then searches the probable locations almost 30 per cent more efficiently than if it searched randomly throughout the room. Artificial intelligence is used in two ways: on the one hand in image recognition and on the other hand through the use of a language model.

Another special capability of the robot is that it remembers previous images and is able to compare them with new images of its surroundings. If a new object suddenly appears in the kitchen, it recognizes the change with a high degree of certainty (95 per cent) and marks these areas as “highly probable” search locations.

Next step: searching behind cupboard doors

In the next step, the TUM scientist and board member at the Munich Institute of Robotics and Machine Intelligence (TUM MIRMI) also wants to search for objects that are in a drawer or behind a door. To do this, however, the robot will not merely have to draw on knowledge from the internet but will also have to interact with its surroundings.

Robotic arms and hands must open a cupboard and determine whether it opens upwards or sideways and how best to grasp the handle. This will enable the robot to search even in closed spaces such as cupboards or drawers.

The Garmi has evolved: on a stable, mobile base, the upper body of the new care-assist robot is attached to an extendable lifting column with arms located on the right and left-hand sides of the column. Above the arms is a head with alert eyes that blink from time to time. The new generation of Garmi has various sensors: cameras are mounted at eye level to detect movements in the environment, a lidar at leg height keeps objects in the immediate vicinity at a sufficient distance, and in future, 3D cameras will secure and coordinate the movements of the two arms. There is also a screen at chest height.

“The new Garmi understands language, develops a plan independently and brings a patient something to drink,” says Alexander König, whose team developed and implemented the new platform. Based on the new design, the first forward-looking functionalities have now been developed. The MIRMI professor says: “A robot must be functional and operable, but must also have an appealing appearance. That’s why we are collaborating with design experts.”

Robotics engineer König sees his Garmi research team as an integrator that brings technology and design together. This includes, for example, precise grasping functionality (perception) and the ability to arrive at the exact location where a task is to be performed (navigation). The design should also support people in interacting and communicating with the robot while conveying trust and safety.

Bavaria’s health minister Judith Gerlach said: “The new development approach of Garmi is extremely exciting. At its research site in Garmisch-Partenkirchen, TUM is creating innovative solutions that are ideally suited to relieving the burden on nursing staff. At the same time, the quality of life of people in need of care can be improved.”

TUM Vice President Gerhard Kramer adds: “The geriatronics research team in Garmisch has once again demonstrated that it is closely attuned to the needs of caregivers and older people. This is the only way to find solutions that ultimately provide optimal support for those in need of care. It’s great to see that the new Garmi was developed in such close collaboration with the Munich Design Institute.”

Needs of caregivers, patients and clinicians

“While the original Garmi was designed as a versatile research platform, the new Garmi has been specifically developed for the care context,” says Annette Diefenthaler, Professor of Design and Transdisciplinarity and Director of the Munich Design Institute (MDI), who worked with an external partner to develop the design of the new robot. Several workshops attended by carers, elderly people, doctors and robotics researchers provided important insights for the design of the new generation of assistance robots.

‘Empathetic, competent, professional, trustworthy and friendly’ were among the characteristics listed on the wish list of participants at a design workshop held at the end of last year. Despite the technology involved, it was clear that acceptance and emotional closeness to a care robot play a decisive role. This is one of the reasons why it is clad in loden, a traditional wool fabric common in the Alpine region: “The fabric combines tradition and the future, gives the robot warmth and regional character and makes it more trustworthy,” comments Prof. Diefenthaler.

A friendly being that controls technology

The robot is more like a mobile platform than a humanoid. “But it was clear to us from the outset that it should come across as friendly and approachable – with subtle human-like features,” says Diefenthaler. The new platform does not look like a human being: “It’s a friendly creature that controls technology. This allows the machine to fade into the background while the robot creates an emotional connection.”

The new Garmi can pick up objects from the floor, but also retrieve them from up high. Unlike the first-generation Garmi, the face and screen are separate. In future, when a doctor is connected for a remote examination, their head will appear on the screen, just like in a video call. The next step is to make the new Garmi safe for use in both care facilities and the home environment of senior citizens. Bringing a drink to a thirsty person is only the first step. “Helping people get up, enabling communication and participation in social life, reminding them to take their medication – the possible applications are wide-ranging,” says Prof. König.

Data collected using the gloves – which cost around £50 to make – could be used to teach robots to use their hands in similar ways to humans, the team says.

Developing robots with greater dexterity could improve their ability to be used in challenging applications, such as remote surgery, virtual reality and carrying out tasks in space.

Each glove is equipped with a range of sensors that can detect subtle movements, such as finger bending and changes in the spacing between fingers – a feature that similar, existing technologies tend to lack.

The sensors, housed in silicone and composed of electrodes made of liquid metal, detect movement by measuring changes in the amount of electrical charge – known as capacitance – stored by their electrodes. Changes to capacitance are produced when the fingers of the glove bend or the distance between them changes.

Researchers from the University of Edinburgh tested their design by collecting hand gesture data from six participants. While wearing the glove, each participant performed 30 different hand gestures, which the sensors detected with more than 99 per cent accuracy.

To investigate the sensors’ ability to track even more complex hand motion, researchers tasked participants with performing random movements whilst wearing the glove.

The team used cameras to track the hand at the same time, producing a comparison dataset to test the glove’s accuracy. Their results show that the sensors can accurately reconstruct hand shape and movements that closely match the comparison data, outperforming current technologies by almost 10 per cent.

Following on from this study, researchers are seeking to improve the glove’s sensing capabilities by integrating technology to mimic the human hand’s sense of touch across the whole palm.

The research was presented at the 2025 IEEE/RSJ International Conference of Intelligent Robots and Systems in Hangzhou, China – one of the largest and most impacting robotics research conferences worldwide. The work was supported by the European Research Council, which has also recently awarded the research team a Proof of Concept grant to commercialise its related, flexible electronic skin technology.

The team is working with Edinburgh Innovations, the University’s commercialisation service, to translate these proprietary technologies into real-world impact. The focus is on next-generation robotics, particularly dexterous and humanoid robots, where rich whole-body sensing is critical for safe, intelligent interaction with the physical world. Target applications also span a range of use cases from health care, such as surgical robotics and compliant protheses, to virtual and augmented reality and wearable technologies.

Dr Yunjie Yang, of the University of Edinburgh’s School of Engineering, who led the study, said: “By using highly stretchable liquid metal electrodes, we can capture the continuous, fluid transition of a hand in motion. This high-fidelity gesture data is the missing link needed to teach robots not just how to hold an object, but how to manipulate it with human-like agility and grace.”

Through a dual-city setup connecting the Beijing Humanoid Robotics Data Training Center and the IROS exhibition booth in Hangzhou, a RealMan trainer in Beijing remotely controlled humanoid robots at the booth to perform complex interactive tasks such as handing over a towel and passing fruit.

Accelerating embodied intelligence innovation

RealBOT is a comprehensive open platform designed to accelerate embodied AI innovation. It integrates advanced motion control, multi-dimensional perception, and precision manipulation, empowering researchers and developers to experiment, prototype and advance embodied AI applications.

Built for high-quality data collection, RealBOT leverages over one million multimodal data samples collected across ten real-world application scenarios from RealMan’s Data Training Center. This enables more robust model training and faster deployment across industries. Key technical advantages include:

• Full-stack in-house development: Proprietary actuator and control technologies ensure optimised performance and reliability.
• Flexible compute support: Compatible with both NVIDIA Jetson Orin and Digua RDK S100 platforms.
• Multisensor fusion perception: Integrates depth and wide-angle cameras, LiDAR, IMU, and microphone arrays.
• Compact design for narrow spaces: Excellent mobility and precision operation in confined environments.
• High-degree dexterity: 21 active DOFs with support for dexterous hands and adaptive grippers.
• Open ecosystem: Compatible with various mainstream vision systems and gripper models.

With its ultra-lightweight architecture, RealBOT lays the groundwork for scalable humanoid systems and high-quality data generation, empowering embodied AI to move from lab research into homes, factories, and service industries worldwide.

Driving global collaboration in embodied AI

The Beijing Humanoid Robotics Data Training Center, built by RealMan, now serves as the backbone for high-quality data generation and AI training. Featuring over 100 robots across 10 real-world environments, it enables the continuous collection of large-scale multimodal datasets that support RealBOT and global research partners, building an open, collaborative ecosystem for embodied intelligence.

Image courtesy of Tara Winstead from Pexels © 2021

Humanoid robots are moving closer to real-world deployment – and their progress depends on physical intelligence and real-time reasoning. With the recent announcement of general availability of NVIDIA Jetson Thor, Analog Devices (ADI) is further accelerating the development of humanoids and autonomous mobile robots (AMRs).

Combining ADI’s edge sensing, precision motion control, power integrity and deterministic connectivity with Jetson Thor’s compute capabilities, Holoscan Sensor Bridge and Isaac Sim, creates a path to scale reasoning-enabled robots from simulation to deployment.

Jetson Thor redefines what’s possible for robotics. With a NVIDIA Blackwell GPU, transformer engine, Multi-Instance GPU (MIG), a 14-core Arm Neoverse V3AE CPU, and up to 128GB of LPDDR5X memory, it delivers 2070 FP4 TFLOPS server-class AI compute in a mobile power envelope. Its high-throughput I/O, including 4×25GbE, provides the bandwidth needed to fuse dense multimodal sensing in real time.

This capability makes NVIDIA Jetson Thor the first platform to run robotics foundation models at scale, from vision-language to vision-language-action models, enabling robots to move beyond perception into reasoning and physically intelligent behaviour. That aligns directly with ADI’s R&D focus: sensing, perception, control and connectivity that makes such reasoning actionable in the real world with high physical accuracy.

“For the first time, robots can understand complex tasks. ADI delivers the precision physical substrate which, combined with NVIDIA Jetson Thor’s reasoning, responds to real world physics in real time,” says Paul Golding, VP of Edge AI, ADI. “Together, we’re taking humanoids from simulation to shift ready deployment.”

The key to reasoning and physical intelligence

Robotics foundation models compress decades of challenges into perception-rich humanoids capable of dexterous, human-speed manipulation. But their real breakthrough is in reasoning: integrating multimodal inputs to plan, adapt and act in real time.

As noted on our third-quarter 2025 earnings call, ADI’s content opportunity grows with this shift. Every joint needs precise current, position and torque control. Every contact needs tactile and sensory feedback. Humanoids require multiple perception nodes. Each node is a signal chain, perception stack, and power-management opportunity that must run deterministically and with low latency – ADI’s strength.

Closing the Sim2Real gap

ADI is embedding robotics foundation models into the ADI development stack, closing the Sim2Real gap so its hardware behaves in NVIDIA Isaac Sim as it will in the real world. The goal is to build the most physically accurate robotics content in NVIDIA Isaac Sim, enabling teams to iterate at simulation speed and then scale seamlessly to real systems with ADI hardware and NVIDIA Jetson Thor.

Physical intelligence fuses sensing, actuation and policy learning and reasoning so robots can execute precise industrial tasks. It demands high-fidelity edge sensing, energy efficient and functionally safe power, deterministic connectivity to central compute, and a digital twin that closes the Sim2Real loop.

This can now be achieved: NVIDIA Jetson Thor is the compute substrate, and ADI delivers the signal chain fidelity, power integrity, and content that make it actionable.

“With NVIDIA Jetson Thor as the brain and ADI’s high-fidelity sensing, signal-chain fidelity and deterministic connectivity as the nervous system, we take robots from NVIDIA Isaac Sim to the factory floor with physical accuracy – faster,” says Golding

The future of reasoning and physical intelligence

ADI sees growing demand for humanoids across logistics, agriculture and surgical robotics. Frontier use cases include dexterous manipulation of cable assemblies in data centres and automotive manufacturing – tasks that reward speed, precision, and repeatability. ADI’s collaboration on digital twins and policy training in NVIDIA Isaac Sim will address this demand and shorten timelines from concept to production humanoids using ADI’s stack with NVIDIA Jetson Thor.

The same stack – high-fidelity sensing, deterministic connectivity, and digital-twin grounded policy training – extends to other platforms, such as AMRs, where ADI is working with NVIDIA to incorporate ADI perception into cuVSLAM via its IMUs, depth sensors and wheel encoders.

The field of robotics has transformed drastically in this century, with a special focus on soft robotics. In this context, origami-inspired deployable structures with compact storage and efficient deployment features have gained prominence in aerospace, architecture, and medical fields. Thus far, experts have mainly utilized paper, thin glass, and polymers as foldable materials for such applications. However, fibre-reinforced polymer (FRP) – a state-of-the-art alternative – remains underexplored in terms of the accuracy and reliability of the fabrication process.

Addressing this knowledge gap, a team of scientists from Pusan National University, led by Dong Gi Seong, an associate professor in the Department of Polymer Science and Engineering, has proposed a multi-resin dispensing process for FRP fabrication that combines rigid and flexible epoxy resins, allowing for the precise patterning of mechanical properties within a monolithic structure. Their work was made available online on 30 June 2025 and has been published in Volume 305 of Composites Part B: Engineering journal on 1 October 2025.

Dr. Seong highlights the main contribution of their work, stating: “Our novel and efficient technique for fabricating composite materials that enable flexible bending while maintaining strong structural performance – an advancement that has not been previously reported in the literature – overcomes the limitations of traditional single-resin systems and manual processes, enabling selective control of rigidity and flexibility within the monolithic composite.”

In this way, the researchers achieve flexible bending without compromising the structural integrity required for advanced deployable structures in various applications including rigid-soft robotics applications. They demonstrate the potential of their approach to produce durable, high-performance FRP composites through the successful fabrication of a triangulated cylindrical origami structure.

These composites exhibit a flexural modulus of 6.95 GPa in rigid sections and 0.66 GPa in foldable sections, with a bending radius of less than 0.5 mm, ensuring both flexibility and stability under repetitive cycles with high strain tolerance. Furthermore, the fabricated structure is lightweight, mechanically robust, and capable of complex motions such as extension, compression, bending, twisting, and deployment, making it ideal for a wide range of applications.

According to Dr. Seong, their innovation can lead to significant breakthroughs in various futuristic fields of science and technology. “Its applications include robotic parts including joints to create a Transformer-like robot, deployable parts for space applications such as deployable solar panel and solar sailing spacecraft, foldable and rollable electronics substrate or cover, architectural designs for tent, military or emergency shelter, as well as transformable wheel for next-gen vehicles.”

This research lays the groundwork for compactly stored structures that can be precisely deployed and retain their mechanical durability, leading to long-term societal impacts, including but not limited to enhanced reliability of emergency tents and wearable protective equipment for disaster response and improved transportation efficiency for low Earth orbit satellite systems, accelerating the global rollout of space-based internet.

In the long term, the proposed technology can pave the way for applications in robotics where unified rigid–soft structures can enable power suits, humanoid joints, and adaptive electronics, as well as guide viable material choice for transformable wheels and adaptive structure, enabling energy-efficient mobility systems compared to heavier metal components.

Ultimately, this work could serve as the foundation for next-generation technologies that demand both deployability and durability in everyday life.

When TUM researcher Julia Fleckenstein works with apprentices from the Munich-Ebersberg Construction Guild to erect a wall, a robot is always on hand. Without it, it would be impossible to lay the bricks for the outer layer of the wall. Of the 1,700 bricks used, more than 200 are not positioned exactly above each other. “They are rotated out from the wall at different angles,” says the architect, who holds the TUM Professorship of Digital Fabrication. The reason for this is that the wall is climate-optimised. A digital design configurator knows how shaded or sunny the location is where the wall of a house is to be built and calculates precise, climate-optimized positions for the individual bricks.

The robot stores a digital twin of the wall. As a result, the logic of robot assembly is directly integrated into the design process. “The robot is like a new colleague,” says Fleckenstein. The robot arm is equipped with a gripper and mounted on a mobile base to move left and right as needed. This allows it to reach any point on the approximately 4 x 2.50 metre wall.

Robot included for the first time

The robot was developed at TUM to work on construction sites alongside humans. “It makes sense to build this way,” says Markus Bruckner, a trainer for bricklayers and plasterers at the Guild: “The robot provides precision where humans reach their limits.”

Rather than replacing skilled craftsmen and craftswomen, it complements their skills. Three of Bruckner’s apprentice bricklayers worked on the wall. “It took some getting used to at first when a robot arm suddenly started working alongside us,” says bricklayer apprentice Dragan Stanojevic, who will complete his training next year: “Now it’s easy to imagine it.”

Simulated in advance on the computer

The project, which is funded by the Bavarian transformation and research foundation “Climate Active Envelopes”, is also based on the idea of simpler construction, for example, using only bricks. Instead of complex wall structures with different materials, the trainees lay bricks in several layers one behind the other. The wall is now “four heads deep,” in Bruckner’s words – a total of 55 cm. That is 20 to 25 cm more than usual.

“Weather-resistant clinker bricks or impregnated bricks are used on the outside, while insulating bricks should be used on the inside, initially shown here with perforated bricks,” says Fleckenstein. Master mason and construction technician Bruckner adds: “Bricks allow for simple and sustainable construction – and with monomaterial constructions, we are also thinking about easier dismantling and reusability.”

Robots on the construction site of the future

“The workshop makes it clear that collaborative robotics does not mean replacing craftsmanship, but rather expanding it in a targeted manner,” says Kathrin Dörfer, Professor of Digital Fabrication at TUM, who initiated the workshop together with Laura Lammel, Master Craftsman at the Munich-Ebersberg Construction Guild: “It is precisely the interplay of digital planning, robotic execution and craftsmanship that creates new possibilities in the construction process.”

This opens up prospects for trainees in a future-proof craft which, far from being displaced by new technologies, will actually be strengthened.

They have prototyped a new software system which can overlay a wide range of new virtual behaviours on commercially-available robot pets and toys which are designed to look like animals and mimic their actions.

The system, called Augmenting Zoomorphic Robotics with Affect (AZRA), aims to address the shortcomings of the current generation of these ‘zoomorphic’ robots, which often have very limited options for interactivity.

In the future, AZRA-based systems could enable older robot pets, and even previously non-interactive toys like plush dolls, to provide experiences which are much closer to those provided by real animal companions.

The richer experiences AZRA enables could help provide more pet-like experiences for people who are unable to keep real animals for reasons of health, cost or restrictions on rental properties.

When users of the AZRA system wear augmented reality devices like Meta’s Quest headset around their robot pets and toys, it projects a sophisticated overlay of virtual facial expressions, light, sound and thought bubbles onto the toy’s surfaces and surroundings.

AZRA is underpinned by a sophisticated simulation of emotions based on studies of real animal behaviour. It can make robots seem more convincingly ‘alive’ by imbuing them with moods which fluctuate unpredictably and can be affected by the touch or voice of their owner.

Eye contact detection and spatial awareness features means it knows when it is being looked at, and touch detection enables it to respond to strokes – even protesting when it is stroked against its preferred direction. It can request attention when ignored, or relax peacefully when sensing its owner is busy with other activities.

The system can also adjust the enhanced pet’s behaviour to better suit their owners’ personality and preferences. If users are high-energy and playful, the robot slowly adapts to become more excitable. In quieter households, it becomes more relaxed and contemplative.

The team say their research could also help cut down on electronic waste by reducing the likelihood of robot pets and toys being disposed of after their owners become tired of them.

The development of AZRA will be presented as a paper at the 34th IEEE International Conference on Robot and Human Interactive Communication in the Netherlands on 26th August.

Dr Shaun Macdonald, of the University of Glasgow’s School of Computing Science, is the paper’s lead author and led the development of AZRA. He was initially inspired to develop the system after receiving a less-than-inspiring gift. He said: “I was given a little robot pet that had a very basic set of movements and potential interactions. It was fun for a few days, but I quickly ended up losing interest because I had seen everything it had to offer.

“I was a bit disappointed to realise that, despite all the major developments in technology over the last 25 years, zoomorphic robots haven’t developed much at all since I was a child. It’s all but impossible to build a relationship with a robot pet in the way you might with a real animal, because they have so few behaviours and they become over-familiar very quickly.

“As a researcher in human-computer interaction, I started to wonder whether I could build a system which could overlay much more complex behaviours and interactions on the toy using augmented reality. Being able to imbue older robots and pets with new life could also help reduce the carbon footprint of unwanted devices by keeping them from landfill for longer.”

Dr Macdonald used a simple off-the-shelf zoomorphic pet, the Petit Qoobo, as the basic real-world platform on which to overlay the augmented reality elements during the development of the system.

Guided by previous research into the emotional needs of dogs, Dr Macdonald developed Zoomorphic Robot Affect and Agency Mind Architecture, or ZAMA. ZAMA provides the AZRA system with a kind of artificial emotional intelligence, giving it a series of simulated emotional states which can change in response to its environment.

Rather than simple stimulus-response patterns, the system provides the augmented reality pet with an ongoing temperament based around combinations of nine personality traits including ‘gloomy’, ‘relaxed’ or ‘irritable’. It has daily moods that fluctuate naturally, and a long-term personality which develops over time through interactions with its owner.

It simulates desires for touch, rest, food, and socialisation which are subtly randomised each day. When its needs aren’t met, the AR robot will actively seek interaction, displaying emojis and thought bubbles to communicate what it wants.

The researchers are already working to explore the future potential of the technology, including participatory studies where volunteers can interact with the robot and then adjust its emotional parameters in real-time to explore what feels natural versus artificial in robot behaviour.

Dr Macdonald added: “AZRA turns a robot from being a device that I almost entirely choose to interact with into a device which can engage me in interaction itself. It feels more like me and another entity attempting to interact and communicate, rather than me make-believing almost all of that interaction myself.

“One of the main advantages of this system is that we don’t have a fixed ‘this is how this should work’ approach. What we have is a really great development test bed where we can try different ideas quickly and see what works. As AR glasses become more mainstream, this could become a way to breathe new life into existing robots without having to replace them entirely.”

Dr Salma ElSayed of Abertay University and Dr Mark McGill of the University of Glasgow are co-authors of the paper. The team’s paper, titled ‘AZRA: Extending the Affective Capabilities of Zoomorphic Robots using Augmented Reality’, will be presented at the IEEE RO-MAN 2025 conference at the Eindhoven University of Technology in the Netherlands on Tuesday 26th August.