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Short biography

I received a PhD in robotics from the Faculty of Electrical Engineering, University of Ljubljana, Slovenia in 2015. I conducted my PhD studies at the Department for Automation, Biocybernetics and Robotics, Jožef Stefan Institute in Ljubljana from 2011 to 2015, and at the Department of Brain-Robot Interface, ATR Computational Neuroscience Laboratories in Kyoto, Japan in 2013 and 2014. I was with the Human-Robot Interfaces and Physical Interaction Lab, Advanced Robotics, Italian Institute of Technology in Genoa, Italy from 2015 to 2018. Since 2019, I am an Assistant Professor at the Department of Cognitive Robotics, Delft University of Technology in the Netherlands.


CONTACT: l.peternel@tudelft.nl

Cognitive Robotics, TU Delft
Mekelweg 2
2628 CD, Delft
The Netherlands

My vision

I have always been fascinated by robotics and its impact on human society. While the engineering side of robotics has been my passion from early childhood, I gradually became more and more interested also in the impact of robots on human society. Therefore, focus on the control of physical human-robot interaction and explore its various application areas, such as collaborative industrial manipulators, teleoperation, humanoid robots and exoskeletons. My primary drive in this is to move the robots out of the highly controlled industrial environments and furnish them with the ability to physically interact with humans in unstructured and unpredictable environments. However, the ability to physically interact with the humans and environment in a safe manner is not enough for me. In my vision, the robot should be able to meaningfully collaborate with the humans to perform various tasks, learn from the humans during the collaboration, and dynamically adapt to ongoing changes in the environment.

In hazardous, hard and mundane tasks, I see that human-robot collaboration is merely a transitional solution until we achieve robot-robot collaboration with comparable results, since at the moment and in near-future the robot artificial intelligence (AI) is still way inferior to human cognitive capabilities. Therefore, in such tasks, my vision is to combine the advantages of the robot (i.e., high speed, payload and precision) with human strong points (i.e., superior cognitive capabilities and adaptability). Nevertheless, on a society level and in many other daily tasks, I believe the human-robot collaboration principle and keeping humans involved in work is essential. I think robots should not take over all of the work from humans, since I see work as one of the key elements of society; the element that gives us a strong sense of purpose and our value to human society. Without human-robot teamwork, I feel that human society cannot properly function, and humans not having meaningful work can be detrimental to individual humans’ mental and physical health.

My view on research

As a roboticist, I consider myself an engineer first and foremost, since robotics is essentially an engineering discipline, not a scientific discipline. Engineering is often looked down on (compared to science) and confused with implementation and technician work. I am sure everyone heard of the expression "rocket science". Yet, rocketry is not science but engineering! So what is the difference between engineering and science?

In my view (see the figure), these are two complementary and equally important research processes. Simple distinction: science explains something that already exists but we do not yet understand, while engineering creates/invents something that does not yet exist. Examples of scientific process output: explaining gravity, understanding the human brain function, and comparison/analysis of the performance of two systems. Examples of engineering process output: a new robot design, a new control method/algorithm, and a new device (e.g., an aeroplane). Yes, there are animals that can fly in nature but none of them is really structured, propelled, or flying in the way an aeroplane does.

Engineering and science complement each other by using each other's outputs as inputs for the respective new research processes. For example, the science leading to a better understanding of light reflection in nature was then used by engineering to create a microscope (a device not existing in nature at that point). Then, the microscope was used as a tool that enabled new scientific discoveries (i.e., understanding/insights) in biology that were not possible before. Therefore, engineering and scientific processes close in a circle and are dependent on (if not essential to) each other.