Mustafa Suphi Erden

My research interests include physical human-robot interaction, assistive robotics, skill assistance, mechatronics design, medical robotics, walking robots, and machine learning. I have been the PI of the EPSRC funded first-grant project "Understanding Laparoscopy Skills for Robotic Training and Assistance" (£124,958), and the Rail Safety and Standards Board (RSSB) funded "Cab Front Cleaning Robot Project" (£35,714). Three of my PhD students are partially/fully funded by industry (RACE-UK Atomic Energy Authority, £33,000; RSSB, £136,000). I have been supervising 1 post-doc and 4 PhD students. I also take part in the ORCA project of Offshore Robotics for Certification of Assets.

My main stream research activity is about physical human-robot interaction and assistive robotics. My long term goals are to endow robots with the ability to provide “closed loop robotic assistance to humans”. To achieve this, my research is divided in two parts. On the one hand, I study the way humans perform skills at different levels of skillfulness to better understand when and how to assist. Second, I use the knowledge acquired from observing humans in order to design robotic controllers that can assist humans during physically human-robot interaction. 

In 2011, I was awarded the FP7-Marie Curie Intra-European Fellowship for my project “Skill Assistance with Robot for Manual Welding” [url:http://lasa.epfl.ch/skillassist/]. This project was an outcome of my above mentioned vision, which is composed of understanding human behavior, identifying aspects for assistance, and finally implementation of robotic assistance. In the specific context of this project, I aimed at understanding the differences between professional and novice manual welders by measuring and comparing their hand impedance during welding. Impedance analysis was accompanied by analysis of variations of position signals. Such analyses provided me with quantitative measures of what the novice subjects are missing compared to the professionals in terms of both hand impedance and position variations. My research results clearly indicated inferior impedance levels and larger position variations with the novice welders, which are also indications that the novice subjects needed compensation for larger impedance to overcome the hand tremor occurring while welding. In the assistance phase, I provided this impedance compensation by means of a virtual dynamics that could be implemented with an interactive admittance controlled robot using a force sensor. As the robotic platform, I was using the KUKA Light Weight Robot Arm with a force sensor attached to its end effector. This overall project exemplifies my vision of closing the assistance loop as it starts by analyzing the human behavior (comparing professionals and novices), continues by identifying quantitative measures that can be used for assistance (impedance levels, kinematic variations) and ends up with an assistive robotic system (impedance compensation with virtual dynamics).

Under this topic, currently I research towards developing knowledge of fine manipulation skills used by surgeons, by simultaneous measurement and analysis of hand-impedance, arm muscle activity (EMG measurements) and cortical brain activity (near infrared spectroscopy-NIRS measurements). I aim to provide an explanation of the brain and muscle activity and their effects, hand-impedance, hand/tool kinematics that are required for skilled manipulation. The target application is Minimally Invasive Surgery, which requires highly sophisticated professional skills that can be attained only with special training and years of professional experience. I will use the generated knowledge to develop robotic assistance and robotic training systems, which incorporate an interactive cooperative robot with real time muscle and brain activity monitoring. My research ultimately seeks to develop a robotic assistance system that adapts to the skill level of the subject by monitoring the state of the arm and brain.

I received the B.S., M.S., and Ph.D. degrees in Electrical and Electronics Engineering from Middle East Technical University, Ankara, in 1999, 2001, and 2006. From 2007 to 2012 I was a postdoctoral researcher, successively in Delft University of Technology, the Netherlands; in Ecole Nationale Supérieure de Techniques Avancées-ParisTech, France; in Univ. Pierre & Marie Curie - Paris 6, France. In 2012 I received the European Union Marie Curie Intra-European Fellowship with my project "Skill Assistance with Robot for Manual Welding". Between 2012 and 2014, I was with Ecole Polytechnique Fédérale de Lausanne, Switzerland, with this fellowship. I am an Assistant Professor with the School of Engineering and Physical Sciences at Heriot-Watt University in Edinburgh, UK, since 2015. My research interests include physical human-robot interaction, assistive robotics, skill assistance, mechatronics design, medical robotics, walking robots, and machine learning. I have been the PI of the EPSRC funded first-grant project "Understanding Laparoscopy Skills for Robotic Training and Assistance" (£124,958), and the Rail Safety and Standards Board (RSSB) funded "Cab Front Cleaning Robot Project" (£35,714). Three of my PhD students are partially/fully funded by industry (RACE-UK Atomic Energy Authority, £33,000; RSSB, £136,000). I have been supervising 1 post-doc and 4 PhD students.