An emerging network of mutualistic technologies is beginning to present a set of technologies that reinforce each other and improve their capabilities and utility across industries and applications.
Robotics stand to move beyond mainly industrial applications towards a wide range of logistical, service and consumer applications – with many appliances, furniture and everyday objects possibly featuring robotic elements in the future.
A conceivable future of embedded robotics
Industrial robots have been part of ongoing automation efforts for more than half a century. In past years, humanoid robots have caught the attention of manufacturers and investors, but some engineers envision unobtrusive – also ambient or integrated – physical artificial intelligence (AI), integrating robotics into everyday objects to assist users in dedicated tasks.
Scientists at Carnegie Mellon University, for instance, are researching a wide range of robots, including autonomous drones and vehicles, off-road robots and moon rangers, and humanoid robots. But the Human-Computer Interaction Institute is investigating “combining AI and robotic mobility … to turn everyday objects into proactive assistants”.
The researchers look at mundane objects such as staplers that can move across a table, for instance. Utensils and other household items can transform “into assistants that can observe human behaviour, predict interventions and move across horizontal surfaces to help humans at just the right time”, such as shelves proactively unfolding to provide a surface to sit down shopping bags when users enter the kitchen after a grocery run.
Assistant professor Alexandra Ion explains the objective: “Our goal is to create adaptive systems for physical interaction that are unobtrusive … blending into our lives while still dynamically adapting to our needs. We classify this work as unobtrusive because the user does not ask the objects to perform any tasks. Instead, the objects sense what the user needs and perform the tasks themselves.”
A range of competing and complementing visions of the future of robotic devices exist. What they have in common is that they rely on – to one degree or another – bundling increasingly powerful, reliable and inexpensive technologies: sensors, AI, extended reality (XR) and robotics are opening multiple pathways to embed automation and smart robotics for practically all commercial applications.
Sensors for robotics proliferate
Sensors are proliferating and diffusing to every corner of the commercial landscape. The growing sensor market reflects the increasing demand mutualistic technologies generate. Market research firm IDTechEx expects the market for sensors to grow by two-thirds between 2026 and 2036.
“Mega-trends driving sensor innovation today include AI and datacentres, internet of things (IoT), Industry 4.0 and robotics,” reports IDTechEx, with future mobility, adoption of wearable technology and the commercialisation of 6G also mentioned.
Industrial suppliers are driving the market development. Bosch, for example, showcased a new solution at CES 2026 in January of this year, stating: “The BMI5 motion sensor platform targets a range of applications, including immersive XR, robotics and wearables.” The company is highlighting use cases of platform variants for XR headsets and glasses as well as robotics and XR controllers.
AI empowers robotics
Stanford University’s Emerging technology review 2026 highlights substantial potential to “advance complex robotic systems, but the speed of future advances will depend on the availability of high-quality training data and the systematic integration of data-rich foundation models, simulated interactions between robots and their environment, and understanding of the real physical world.”
The study authors note: “Simulations add data but lack real-world complexity, requiring costly calibration. To address this, a hybrid strategy of blending advanced AI methods with proven engineering approaches is necessary.” The report also mentions AI as a crucial enabler for humanoid robots.
Commercial developments reflect the review’s conclusions. Hyundai Motor Group showcased its efforts in AI-enabled robots at CES 2026 – including humanoids, quadrupedal robots, delivery robots and robotic wearables.
The company’s AI Robotics Strategy intends to partner “humans and co-working robots to commence the era of AI Robotics, starting in manufacturing environments”. Hyundai also wants to partner with global AI vanguards to innovate physical-AI solutions.
Digital twins improve robotics
Extended reality – particularly digital twins – will change the nature of robotics and how engineers will design, maintain and operate robotics.
Government organisations have noticed the potential these technologies have. The Healey-Driscoll Administration in Massachusetts partnered with the Massachusetts Technology Collaborative’s (MassTech) Innovation Institute to award grants via the Massachusetts Robotics Digital Twin Initiative. The initiative is awarding up to $2m to support robotics and research companies to create robots and their digital-twin representation.
Pat Larkin, director of the MassTech Innovation Institute, says: “Robotics evolves through experimentation. However, prototypes often cost upwards of hundreds of thousands of dollars and can take years to develop … The Digital Twin Library will allow for low-risk collaboration.
“[The partnership is] seeking proposals for novel robot designs and applications from entrepreneurs and research groups willing to contribute to the MA Robotic Digital Twin Library. Preference will be given to groups whose robotic application targets manufacturing, logistics, education or physical AI research.”
Industrial equipment manufacturers explore already related applications. Komatsu, for example, leverages digital twins to simulate robotic welding tools in the factory environment they are operating in. The twins enable engineers to evaluate how the robots will move and weld while working alongside factory workers. The virtual environment allows quick, inexpensive changes to setups to improve solutions before they are getting finalised in real-world applications.
Digital twins also support work on construction sites. Jason Anetsberger, director of customer solutions at Komatsu North America, explains the process: “We are measuring and monitoring the production of individual machines and trucks – how much they haul, how much earth they moved … But we’re also able to simulate questions like, ‘What should that machine be able to move?’, and then think about how that plays out in terms of project schedules.”
Finally, Komatsu is using digital twins to monitor and better understand mining operations. Visibility is limited and conditions are hazardous in mines. Combining real-time sensor data that help create intuitive visualisations to monitor operations and identify potential issues is a crucial safety consideration.
Ramodh Rangasamy, global product manager at Komats’s Mine Site Technologies, says: “Digital twins help bring together data from equipment, sensors and people into a single view of the mine. That view helps customers understand where their assets are and what they’re doing, as well as where their people are, what they’re doing and what are the conditions of the working environment.”
Splicing robotics with AI and XR
Mutualistic technologies engage in many ways, with AI and XR advancing robotics simultaneously and in combination.
At the beginning of this year, a team of researchers from Stanford University and Princeton University launched MedOS, an “AI-XR-Cobot World Model”. The researchers use AI, AR, VR and robotics to support medical and healthcare personnel. Via smart glasses and robotics equipment, the system can develop an understanding of complex processes and environments, with trained physicians then planning and executing procedures. The researchers believe that robots can become part of everyday hospital activities and that AI and XR can provide an interactive fabric between doctors and machines.
Le Cong, co-leader of the interdisciplinary project and an associate professor at Stanford University, says: “The data layer enables us to build the world model with the spatial intelligence to allow robotics to work with humans today rather than wait for fully humanoid robots. There are very few robots in hospitals now other than [Intuitive Surgical’s] da Vinci. We want to bring robots into every single part of medicine.”
Industrial players already investigate use cases that take advantage of AI, XR and robotics. Samsung Heavy Industries (SHI), for example, is exploring the use of XR and robotics to establish smart shipyards with sophisticate automation of shipbuilding. The shipbuilder is cooperating with Samsung Electronics to leverage XR technology, with a demonstration visualisation showcasing the use of the technology in ship inspections.
Lee Dong Yeon, vice-president at the Marine Research Institute of Samsung Heavy Industries, states: “With this cooperation, Samsung Electronics XR technology will fuse Samsung Heavy Industries’ ship construction site utilisation solution and content development know-how to accelerate the implementation of smart shipyards and contribute to strengthening ship manufacturing competitiveness.”
SHI also entered an agreement with Rainbow Robotics, a manufacturer of collaborative robotics equipment, including HUBO-2, a humanoid robot. SHI and Rainbow Robotics intend to create AI-enabled welding robots that can work autonomously on shipbuilding tasks. SHI is investigating the combination of AI, XR and robotics on various fronts.
Physical AI, sensors and digital twins open a new industrial world
Advances across all mutualistic technologies have moved the idea of physical AI to the forefront of practitioners’ attention. Physical AI in industrial applications will ultimately inform the potential for embedded, unobtrusive robotics across economic sectors.
Rahul Garg, global vice-president of industrial machinery at Siemens Digital Industries Software, outlines new industrial realities that call for advanced robotics, stating that new levels of flexibility require “AI that can understand and interact with the real world”.
He added: “In other words, physical AI. Physical AI refers to the application of artificial intelligence beyond the digital realm, where AI systems can perceive, reason and act in the physical world in real time. It combines advanced sensing technologies (such as vision, audio, depth and motion), increasingly capable industrial AI models and physical systems such as robots and machines.
“[But] achieving an AI model that can process complex multi-sensory data and reach reliable conclusions about actions to take is not an easy task. Collecting and managing the data required to train a physical AI model, along with an entire, real-world training environment would be impractical, if not impossible, without the comprehensive digital twin.”
Martin Schwirn is the author of ‘Small data, big disruptions: How to spot signals of change and manage uncertainty’ (ISBN 9781632651921) on foresight and horizon scanning. Schwirn has advised companies internationally for SRI International and Business Finland. He is a strategy and innovation consultant for Global 2000 companies.
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