Modern construction and industrial environments are becoming increasingly automated, yet operating heavy-duty machines in unstructured or changing conditions still requires human involvement. Mahdi Hejrati’s dissertation addresses this need by introducing a control and teleoperation framework that allows operators to “see” and “feel” remote machines and their surroundings as if they were physically present.
At the heart of the framework is a wearable robotic exoskeleton that captures the motion and forces of the human arm. These movements are transmitted to a large hydraulic manipulator, which replicates the operator’s actions in real time. Meanwhile, the operator receives both visual and haptic feedback – forces and sensations that mirror the machine’s interaction with its environment – creating an immersive and natural sense of control. According to Hejrati, the system’s control design ensures that large and powerful machines remain stable and precise, even under communication delays and uncertain environmental conditions. His experiments showed that the approach achieved sub-centimetre motion accuracy, making operation both safer and more efficient.
Beyond safe remote operation, Hejrati’s research also lays the groundwork for learning from demonstration, where robots can learn tasks directly from human teleoperation data. By recording how skilled operators perform complex actions, future machines could use these demonstrations to develop semi-autonomous or fully autonomous behaviors.
“My work brings us closer to a future where heavy machinery can learn from human expertise. It combines the strength and endurance of hydraulics with the intuition and adaptability of human intelligence,” he says.
Herati’s findings could transform the way we operate in hazardous, distant, or high-precision environments, ranging from construction and mining to disaster response. This would make human work safer while enhancing machine capability.
Mahdi Hejrati is originally from Iran and is currently affiliated with Tampere University, Finland.
Public defence on Friday 28 November
The doctoral dissertation of MSc (Tech) Mahdi Hejrati in the field of automation engineering titled Systematic and Robust Control Framework for Immersive Bilateral Teleoperation: Toward Human Skill Transfer to Beyond-Human Scale will be publicly examined at the Faculty of Engineering and Natural Sciences at Tampere University at 13:15 on Friday 28 November at Hervanta campus, Konetalo auditorium K1702 (Korkeakoulunkatu 6, Tampere).
The Opponent will be Prof. Fares Abu-Dakka from New York University Abu Dhabi, Abu Dhabi, UAE. The Custos will be Prof. Jouni Mattila from Tampere University, Finland.