Digital twins: The backbone of robotics deployment 

Robotics is at an inflexion point. Advances in AI, simulation and multimodal sensing are pushing machines beyond scripted routines into a new era of adaptability. No longer confined to repetitive tasks, robots are becoming teammates, capable of adjusting and adding value in real-world environments. 

To overcome barriers to adoption and empower robotics technology to reach its fullest potential, we cannot underestimate the role of digital twin as a critical enabler.

Digital twins are a precise digital representation of the physical world that uses dynamic data to simulate, analyse, monitor, and optimise performance. 

In manufacturing, digital twins allow us to test every movement and process virtually before it happens in reality. They have a home in many industries; for example, aerospace, where engineers and designers pair aircraft engines with digital versions to predict maintenance, track performance and enhance safety. Now, the same approach is reshaping robotics adoption across these key industries. 

As seen in Hexagon’s recent report, Future of robotics 2035: insights from industry leaders, “real-time digital twins trial every tweak before metal moves, slashing waste, [while edge AI makes] split-second calls on-site without risking data privacy.” This ability to combine large-scale simulation with instant, local decision-making “will form the backbone of real-time adaptive manufacturing”, notes Chase Williams, senior consultant at TechInsights. 

Taking the risk out of robotic integration 

Mario Mauerer, global business development manager at maxon Group, comments that “companies often fixate on the physical robot (its dexterity, its sensor stack, its AI) but the real complexity lies in everything that surrounds it”. 

That complexity is especially clear with humanoid robotics. Unlike traditional machines, humanoids are a new technology built to be integrated into existing human environments. They need to navigate tight spaces, work alongside people, and adapt as factory layouts change. Creating digital twins of factories and warehouses, often facilitated by reality capture, gives companies the simulation-ready environments they need for deployment. 

This preparation helps manufacturers answer vital questions up front:  

• Will the robot fit through each aisle?  
• Can it operate safely with human workers? 
• Will it meet productivity targets? 
• Will training programs be successful when the robot is in place? 

By rehearsing virtually, businesses can reduce downtime, cut risk, and speed up deployment. This is driving real-world, measurable results: in Hexagon’s Digital Twin industry report, 49% of organisations using digital twins report improved efficiency, 45% cite better reliability, and 47% see reduced costs. 

Robotics trained ‘by example’ can struggle when conditions such as lighting change. With a digital twin of the factory or warehouse, we can validate training programs can virtually to ensure reliability and successful, adaptive robots when conditions change in practice. 

Williams adds, “over the next five years, we’ll see major growth in co-bot deployment, as well as AI-powered autonomy that enables robots to work in far more dynamic, unpredictable environments. With real-time learning and edge computing, we’ll unlock new possibilities in outdoor robotics, urban navigation, and time-sensitive industrial automation.” 

The edge advantage  

Pairing digital twins with edge AI enables robotics to adapt in real time. Instead of always relying on the cloud, these digital twins can process information locally, make split-second decisions, and keep sensitive data secure. Robotics can carry their own digital twin onboard, helping them avoid collisions and adapt in busy environments.  

A backbone for future transformation 

Digital twins are giving robotics the context they need to integrate safely into human environments – allowing them to complement and enhance workflows. 

Looking ahead to 2035, experts expect robotics to be as invisible as smartphones: a dependable infrastructure layer for key manufacturing processes. Fleets of reconfigurable autonomous solutions will manufacture on demand, with digital twins assessing every change along the way. The result? Less waste, tighter safety protocols, and faster ROI.  

Robotics deployment at scale won’t succeed without trust and precision. Digital twins provide both; making autonomy reliable, safe, and economically beneficial, while ensuring every step a robot makes on the factory floor has already been perfected digitally. 

Dive deeper into the evolution of robotics by reading Hexagon’s Future of robotics 2035: insights from industry leaders. Discover why innovation in robotics is accelerating today, where adoption is gaining momentum, and how it will shape businesses and workers through 2035.