Robotics is inherently interdisciplinary; it weaves together hardware, software, control, perception, AI, and human interaction to build systems that sense, plan, and act in the world. At the University of Twente, the Robotics Centre brings together a network of research groups working across “Robotics for Healthcare,” “Robotics for Industry,” and “Robotics for Society.”
Each course within the MCs Robotics is bound to one or multiple domains. Below, all domains and their purposes are explained.
Robot = "A mechanism that moves in an environment, with at least some autonomy or some interaction".
The domain of the robot’s brain and low-level intelligence
This domain centres on the embedded electronics that make robots “alive”: sensor circuits, microcontrollers, real-time processing, and energy management. Students use the Software Development for Robotics course to bridge hardware and software, learning how embedded firmware, real-time loops, and efficient communication protocols shape a robot’s responsiveness.
Meanwhile, the Embedded Systems Laboratory immerses students in circuit design, sensor integration, and firmware development. These skills enable researchers to create high-precision and energy-efficient robots, whether for the industry, healthcare, or society.
Relevant courses:
The domain of stabilising, regulating, and shaping robot motion
Control engineering is the science that ensures robots behave the way we intend them to. It is where mathematics meets physical reality: turning kinematic models, motor torques, and sensor feedback into smooth, stable, predictable motion.
At the University of Twente, this domain comes alive in Control System Design for Robotics, where students learn how feedback loops keep a robotic arm precise, how a mobile robot stays balanced, or how a drone remains stable even in wind. It’s not just about formulas, it’s about making physical systems behave safely in an unpredictable world.
More advanced topics appear in System Identification with Parameter Estimation and Machine Learning, where students learn to model real systems from experimental data. This is crucial for robots whose dynamics change over time, such as manipulators with flexible joints, soft robots, or wearable exoskeletons.
Relevant courses
The domain of coordinating projects, people, and processes
The Systems Engineering course trains students in structured methods for breaking down large multi-disciplinary projects. They learn how to analyse stakeholder needs, translate them into system requirements, evaluate design trade-offs, and manage the entire lifecycle of a robotic system, from dream to reality. This discipline becomes essential when constructing complex systems such as autonomous vehicles, medical robots, or multi-sensor industrial platforms.
Whether building a rehabilitation robot for a hospital, an industrial inspection drone, or a social companion robot, system engineering ensures that technology aligns with user needs, safety requirements, certification constraints, and long-term maintenance considerations.
System engineering is not about controlling motion; it's about controlling the project.
Relevant courses:
The domain of sensing, interpreting, and understanding the world
Here, raw sensor data is transformed into meaningful insight. The Image Processing and Computer Vision course guides students through techniques to process images, extract patterns, and make sense of visual information. Meanwhile, Robot Perception, Cognition and Navigation delves into how robots build internal maps of their surroundings, fuse multiple sensors, and plan smart paths.
For advanced spatial understanding, Laser Scanning and Point Cloud Processing let students work with 3D data, vital for real-world robots navigating cluttered or dynamic environments.
These courses feed into the University of Twente’s robotics research groups (like Human Media Interaction), enabling systems that can navigate, understand gestures, or interpret complex scenes.
Relevant courses:
The domain of decision-making, adaptation, and learning
In this domain, robots become more than programmed machines: they become learners and reasoners. At the heart of this story is AI for Autonomous Robots: Deep Learning & Reinforcement Learning, where students explore how robots can train themselves to perform tasks, adapt to change, or master complex behaviours.
For those who want to deepen their theoretical foundations, there’s Deep Learning: From Theory to Practice, which teaches how neural networks work in real robotic applications. On the research side, Machine Learning I & II provide tools to build predictive models and controllers.
Relevant courses:
The domain of communication, trust, and social collaboration
Robots don’t always just perform tasks; sometimes they form relationships, assist people, or act as social companions. This domain is embodied in the Human-Robot Interaction & Social AI specialisation.
In Human-Robot Communication, students study how robots and humans can communicate naturally through speech, gestures, or expressions. Tele-presence Robotics explores remote collaboration: how a robot can represent a person at a distance, enabling new forms of social presence. For more design-driven exploration, Social Robot Design invites students to imagine robots that are not just functional, but socially aware, emotionally intelligent, and ethically grounded. These courses connect deeply with the Human Media Interaction research group, where robotics meets psychology, design, and user experience.
Relevant courses:
The domain where robots meet the human body
This domain is deeply human: it focuses on how robots assist, heal, and augment human life. The Robotics for Medical Applications course brings students into the world of surgical robots, rehabilitation systems, and assistive devices. They study how to integrate precise mechanics with safety-critical control and sensitive sensing to build solutions for real clinical challenges. In AI- and Image-guided Robotics: from Theory to Medical Applications, students explore how vision, planning, and AI can support minimally invasive procedures or diagnostic systems.
The Biomechanical Engineering research group at the University of Twente is at the forefront, developing exoskeletons, prostheses, and wearable robots that move in sync with the human body. Through this domain, robotics becomes a force for healing and empowerment.
Relevant courses:
The domain of energy-efficient, eco-conscious robotic design
Sustainable engineering within robotics is about more than reducing energy consumption; it’s about rethinking the entire lifecycle of robotic systems. At the University of Twente, this mindset emerges naturally from the intersection of engineering, design, and societal impact.
Within the Smart Environment Integration Project, you work on a sustainable project that bundles two (or more) technologies together, creating a new innovation.
Sustainable robotics begins with material choices: lightweight structures that reduce energy demand, durable joints that minimise maintenance, and modular components that can be reused instead of discarded. It continues in operation, where algorithms are optimised to consume less power, perception systems are designed to process only the information they need, and robot behaviours are planned to minimise unnecessary movement.
But sustainability also extends beyond the robot itself. Researchers explore how robots can contribute to environmental monitoring, precision agriculture, and circular production lines, systems where robots help society use fewer resources more intelligently. In the Design Lab and across the Robotics Centre, students and researchers are encouraged to ask not only “Can we build it?” but “Should we build it this way?” and “What long-term value does it create?”
Relevant courses:
The domain of flying robotic systems
Here, robotics takes to the skies. The Aerial Robotics course at the University of Twente lets students explore the aerodynamics, control, and navigation of drones. They learn how onboard sensors help with navigation, and how control loops keep a drone stable even in turbulence. This domain connects strongly to other areas: mechanics to design the frame, control to maintain stability, perception to avoid obstacles, and AI to plan autonomous flight paths.
Research at the University of Twente often applies these teachings to environmental monitoring, precision agriculture, or infrastructure inspection, proving that aerial robots are not just futuristic toys, but practical tools for sustainable, high-tech applications.
Relevant courses:
The domain of imagination, prototyping, and turning ideas into impact
Robotics is as much art as engineering, and at the University of Twente, students are encouraged to dream as well as build. In Mastering Tinkering, they explore rapid prototyping, playful design, and unconventional approaches, creating interactive robots, installations, or experimental systems. Human Centred Design teaches how to design with users at the heart, imagining how robots might feel, communicate, or serve in human contexts.
On the more entrepreneurial side, the Robotics Innovation Tournament gives students a structured journey through ideation, prototyping, and pitching, preparing them to found startups or bring innovations to market. This domain is deeply rooted in Twente’s maker culture and innovation ecosystem.
Relevant courses:
The domain of industrial robotics, precision, and automation
In this domain, robots become part of advanced manufacturing, smart production lines, and precision engineering. The course Industrial Robotic Systems explores how robotic arms are integrated into factories, automated production, and quality control.
In the Mechatronics & Physical AI specialisation, students also dive deep into system identification, adaptive control, and robust design so that robots can operate reliably in the harsh, high-precision environment of the high-tech industry. This domain binds together mechanics, electronics, control, and system engineering to deliver real robots in real industrial contexts.
Relevant courses:
The discipline of turning raw information into meaningful insight
The Data Science course equips students with the tools and mindset needed to extract value from data in all its forms. They learn how to collect and clean datasets, explore patterns, build statistical and machine-learning models, and translate complex analytical results into decisions that drive action. This field becomes critical when developing intelligent robotic systems, adaptive medical technologies, or predictive industrial platforms.
Whether analysing sensor streams from an autonomous robot, predicting patient outcomes in a healthcare device, or optimising workflows in a smart factory, data science ensures that decisions are informed, models are validated, and uncertainty is understood and managed.
Relevant courses:
The domain of physical embodiment of robots
This domain is about the mechanical design of robots, including their actuation, kinematics, dynamics, and integration of electronics. Students learn how robotic arms, walking machines, and even drones become real through careful modelling of dynamics, kinematics, and structural behaviour.
A course like Modelling, Dynamics and Kinematics introduces the language of motion, while Design Principles for Robotic and Mechatronic Mechanisms shows how UT researchers translate equations into real prototypes.
In the Robotics and Mechatronics (RaM) group, these principles come alive in systems ranging from industrial manipulators to healthcare-assistive devices. At the University of Twente, mechanics is not only about structure, but about motion that feels trustworthy, precise, and purposeful.
Relevant courses:
The domain of responsible, societal-aware robotics
Robotics does not exist in a vacuum. Engineers can build incredible machines, but those machines will not only have a positive impact. The ELSE course addresses this exact complexity, spread across the academic year with a different focus each quarter.
In the Economics module, students explore how robotics influences industries, production systems, and markets, gaining insight into cost-benefit trade-offs, business models, and the societal value of automation.
The Legal module examines regulations, liability, and safety standards, equipping students to autonomously design robots that comply with current and emerging laws.
In Social, students learn how humans interact with robots, including trust, communication, and accessibility considerations, ensuring that robots are designed with people at the centre.
Finally, the Ethics module challenges students to reflect critically on how robots affect society, considering issues like privacy, job displacement, and responsible innovation.
Through ELSE, students develop the awareness that every technical decision has societal consequences. It teaches them to design not only for efficiency or performance but for fairness, safety, and long-term benefit.