Multilimb Coordination in Human Neuroscience and Robotics: Classical and Learning Perspectives

  • When: October 5th, 2023
  • Where: IROS 2023, Huntington Place in Detroit, Michigan, USA
  • Organized by:
    • Soheil Gholami1 – Ph.D.
    • Kunpeng Yao1 – Ph.D.
    • James Hermus1 – Ph.D.
    • Etienne Burdet2 – Full Professor
    • Aude Billard1 – Full Professor

1Learning Algorithms and Systems Laboratory (LASA), Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland.

2Department of Bioengineering, Imperial College of Science, Technology, and Medicine, London UK

Call for Contribution


Objectives and Contents

The ability of humans to effectively coordinate their limbs in diverse situations, such as manipulating objects, dancing, or playing the guitar, has captivated the attention of researchers from a variety of fields from neuroscience to robotics. Neuroscience researchers often use robotics techniques to model human motor control. Conversely, roboticists strive to use new control and learning algorithms to endow robots with human-like abilities such as regulating many degrees of freedom, behaving in a way that is robust to disturbances, and managing complex contact situations. The interplay of human motor control and robotics has been fruitful, with achievements in inverse optimal control, learning-based methods, and variable impedance control. These existing interdisciplinary studies present new challenges that require further discussion and exploration. This full-day workshop will bring together young and senior researchers at the forefront of human motor control and robotics to discuss the trends and challenges in these fields. Moderated live Q&A panel discussions will provide an opportunity for attendees to discuss open questions and challenges facing the field of behavioral neuroscience and robotics in future research, and to examine how state-of-the-art studies apply these approaches in both fields.

The interplay of human behavioral neuroscience and robotics entails a series of questions for researchers in both fields to be addressed. In particular, this workshop aims at discussing the following questions:

  • How may the central nervous system (CNS) acquire a model of the objective function that underlies control in specific tasks?
  • How does the CNS identify appropriate synergies between limbs?
  • The paucity of data in biology poses a challenge to achieving accurate learning. There is a tradeoff between leveraging prior knowledge and relying on the tabula rasa learning perspective. How can prior knowledge in robotics be incorporated to reduce training dataset size and learning duration? Can robotics draw inspiration from research in Biology to achieve this?
  • Can recent developments in inverse optimal control and inverse reinforcement learning benefit biology in studying how humans acquire objective functions?

To ensure that the workshop content is up-to-date and reflects the current state of the art, we have carefully selected and invited nine experienced researchers who are conducting cutting-edge studies in both behavioral neuroscience and robotics. In two sessions, each presenter will give a 25-minute talk followed by a 5-minute Q&A to provide an in-depth overview of their recent achievements. To encourage active engagement and foster discussion, a 45-minute panel discussion will follow each session, where participants can share their opinions, ask questions, and discuss the challenges and prospects related to the topics covered. By featuring experienced researchers and facilitating interactive discussions, we aim to provide a comprehensive and interdisciplinary perspective on the current state of the art in behavioral neuroscience and robotics.

Our workshop aims to broaden the scope of IROS 2023 by offering a diverse range of topics that bridge the fields of behavioral neuroscience and robotics. Specifically, we will focus on the interdisciplinary field, exploring cutting-edge research on topics including inverse optimal control and reinforcement learning in both human studies and robotics, human skill acquisition, multilimb coordination, synergies, interaction control, and addressing the challenge of paucity of data.


8:45 – 9:00Organizers: Welcome and Introduction
Session 1
9:00 – 9:30Dagmar Sternad: Human control of actions and interactions – a task-dynamic approach to reveal control priorities of humans – and robots
9:30 – 10:00Katja Mombaur: Inverse optimal control to analyze multilimb coordination in sprinting with and without running specific prostheses
10:00 – 10:30Presentations – Accepted Abstract Papers
10:30- 11:00Poster Presentations & Coffee Break
11:00 – 11:30Fabrizio Sergi: Using robotics, neuromuscular modeling, and functional neuroimaging to study the neural control of force and impedance
11:30 – 12:00Bastien Berret: Computational understanding of human motor control to improve interaction with a robotic exoskeleton
12:00 – 12:30Panel Discussion (Session 1)
12:30 – 13:30Lunch
Session 2
13:30 – 14:00Luka Peternel: Ergonomics: from human motor control to human-robot collaboration
14:00 – 14:30Meghan Huber: Human interaction control: linking action and perception
14:30 – 15:00Nidhi Seethapathi: Predictive model of locomotor adaptation to exoskeleton control
15:00 – 15:45Poster Presentations & Coffee Break 
15:45 – 16:15Hyunglae Lee: User-adaptive variable impedance control for enhanced physical human-robot interaction
16:15 – 17:00Panel Discussion (Session 2)
17:00- 17:15Organizers: Closing

Invited Speakers

Dagmar Sternad

Biography. Dagmar Sternad is University Distinguished Professor in Biology, Electrical and Computer Engineering and Physics at Northeastern University. She received her BS and MS in Movement Science and Linguistics from the Technical University and Ludwig Maximilians University of Munich and her PhD in Experimental Psychology from the University of Connecticut. From 1995 until 2008, she was Assistant, Associate, and Full Professor at the Pennsylvania State University in Integrated Biosciences. Since 2008, she holds an interdisciplinary appointment as full professor in the departments of Biology, Electrical and Computer Engineering, and Physics at Northeastern University in Boston. In 2018 she was promoted to University Distinguished Professor. She is also executive member of the Institute of Experiential Robotics and member of the Center for Interdisciplinary Research on Complex Systems at Northeastern. Her research is documented in over peer-reviewed 200 publications in high-impact journals, conference papers, book chapters, and several books. She has had editorial appointments in several scientific journals and was regular member of an NIH study section and two times elected member of the Executive Board of the Society for Neural Control of Movement. Her research has been continuously supported by the National Institute of Health (MERIT award), National Science Foundation, American Heart Association, Office of Naval Research, and others. In 2022, she received a Fulbright Fellowship to spend one semester at the Santa Lucia Foundation in Rome, Italy. In 2023 her student and faculty mentoring was recognized with an Excellence in Mentoring Award by the College of Science at Northeastern.

Link: Google Scholar.

Katja Mombaur

Biography. Katja Mombaur joined the University of Waterloo in March 2020 as Full Professor and Canada Excellence Research Chair (CERC) for Human-Centred Robotics & Machine Intelligence. Prior to coming to Canada, she has been a full professor at the Institute of Computer Engineering of Heidelberg University and head of the Optimization, Robotics & Biomechanics Chair, as well as coordinator of the Heidelberg Center for Motion Research. She holds a diploma degree in Aerospace Engineering from the University of Stuttgart and a Ph.D. degree in Mathematics from Heidelberg University and has worked as a researcher at Seoul National University and at LAAS-CNRS in Toulouse. She has coordinated the European project KoroiBot and has been part of several other European projects such as Spexor, MOBOT, and ECHORD, and still is a partner in the ongoing European projects Eurobench and Agilis, and one of the directors of the HeiAge project in Heidelberg.

Link: Google Scholar.

Bastien Berret

Biography. Bastien Berret obtained his Ph.D. in applied mathematics and computational neuroscience in 2008 from the Université de Bourgogne (Dijon, France). In 2009, he joined the Italian Institute of Technology (Genoa, Italy) as a post-doctoral researcher in the Robotics, Brain and Cognitive Sciences department. In 2012, he was appointed as an Assistant Professor at the Université Paris-Saclay (Orsay, France). In 2017, he became a junior member of the Institut Universitaire de France (IUF). He is now a full professor in Human Movement Sciences at the Université of Paris-Saclay. His research aims to better understand human motor control through modeling and experimentation and to exploit this knowledge to improve control laws in applications involving robotic exoskeletons.

Link: Google Scholar.

Luka Peternel

Biography. Luka Peternel received a Ph.D. in robotics from the Faculty of Electrical Engineering, University of Ljubljana, Slovenia in 2015. He conducted his Ph.D. 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. He 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, He is an Assistant Professor at the Department of Cognitive Robotics, Delft University of Technology in the Netherlands.

Link: Google Scholar.

Megan Huber

Biography. Meghan Huber is currently an Assistant Professor in the Department of Mechanical and Industrial Engineering at the University of Massachusetts Amherst, with adjunct appointments in the Department of Biomedical Engineering and the Manning College for Information and Computer Sciences. She is the director of the Human Robot Systems Laboratory, and her research focuses on understanding how humans and robots can learn through physical interactions with the world and from one another. Meghan received her B.S. degree in Biomedical Engineering from Rutgers University in 2009 and her M.S. degree in Biomedical Engineering from The University of Texas at Dallas in 2011. She recently received her Ph.D. in Bioengineering from Northeastern University in 2016. During her doctoral training, she was a Visiting Junior Scientist in the Autonomous Motion Department at the Max Planck Institute for Intelligent Systems in Tübingen, Germany. She was a postdoctoral research associate in the Department of Mechanical Engineering at the Massachusetts Institute of Technology from 2016-2020.

Link: Google Scholar.

Nidhi Seethapathi

Biography. Nidhi Seethapathi is the Frederick A. (1971) and Carole J. Middleton Career Development Assistant Professor of Brain and Cognitive Sciences at MIT. She earned her PhD in Mechanical engineering from Ohio State University in 2018, where she developed predictive models of naturalistic human locomotion as a Schlumberger Foundation Faculty for the Future Fellow in the Movement Lab. She then worked as a postdoctoral researcher in Bioengineering in the Kording Lab at the University of Pennsylvania developing data-driven tools for autonomous neuromotor rehabilitation, in collaboration with the Rehabilitation Robotics Lab.

Link: Google Scholar.

Fabrizio Sergi

Biography. Fabrizio Sergi is an associate professor of biomedical and mechanical engineering at the University of Delaware, where he directs the Human Robotics Lab. His research focuses on the development of robotic devices for physical interaction with humans, and on their application in neurorehabilitation, movement augmentation, and as advanced tools to study human sensorimotor control. Dr. Sergi has developed a family of MRI-compatible robots that can be used in conjunction with functional Magnetic Resonance Imaging to study the neural substrates involved in the control movements. Dr. Sergi received his B.S., M.S., and Ph.D. degrees in biomedical engineering from the Università Campus Bio-Medico di Roma in Rome, Italy.

Link: Google Scholar.

Hyunglae Lee

Biography. Hyunglae Lee is an associate professor of mechanical and aerospace engineering in the School for Engineering of Matter, Transport, and Energy at Arizona State University. He directs the Neuromuscular Control and Human Robotics Laboratory at ASU. Lee’s research interests include physical human-robot interaction, neuromuscular control of human movement, and robot-aided neurorehabilitation. Lee received his doctorate in mechanical engineering from the Massachusetts Institute of Technology under the supervision of Professor Neville Hogan. Then, he worked as a postdoctoral fellow at the Sensory Motor Performance Program, Rehabilitation Institute of Chicago. Previously, Lee also worked at the Korea Institute of Science and Technology and LG Electronics. He received his BS (Ranked 1st in the class of 2002) and MS in Mechanical Engineering from Seoul National University (SNU). He is a recipient of the Top 5% Teaching Award at ASU Ira A. Fulton Schools of Engineering (2020, 2021), New Investigator Award from the Arizona Department of Health Services (2021), Winner of the Innovation Challenge in WearRAcon (2020, 2021), NSF CAREER Award (2019), Outstanding Paper Award in International Conference on Ubiquitous Robots (2018), Sarah Baskin Award (2014), Finalist for the Best Student Paper Award in IEEE BioRob (2012), Samsung Scholarship (2008-2013), and Top Graduation Award in the School of Mechanical and Aerospace Engineering at SNU (2002).

Link: Google Scholar.


Soheil Gholami

Biography. Soheil Gholami received his B.Sc. and M.Sc. degrees in Control Engineering from Shahed University and K. N. Toosi University of Technology, located in Tehran, Iran, in 2013 and 2016, respectively. He earned his Ph.D. in Bioengineering from the Polytechnic University of Milan (NearLab) and the Italian Institute of Technology (HRII), Genoa, Italy, in 2022, where his research focused on studying the usability and ergonomics of teleoperation interfaces. He is presently serving as a postdoctoral researcher at LASA, EPFL, Switzerland. He primarily focuses on two research projects: investigating motor coordination and human movement augmentation in supernumerary manipulation tasks (funded by the Hasler Foundation) and exploring skills acquisition in microsurgery (funded by the Swiss National Science Foundation). In addition, he is an active participant in the RoBétArmé project, which aims to automate laborious construction tasks in all phases of shotcrete application and bring about a significant transformation in Construction 4.0. His main research interests include human-robot interaction and collaboration, human movement augmentation, and human motor control.

Link: Google Scholar.

Kunpeng Yao

Biography. Kunpeng Yao received the B.Sc. degree from Shanghai Jiao Tong University (SJTU), China, in 2013; the M.Sc. degree from the Technical University of Munich (TUM), Munich, Germany, in 2017; and his Ph.D. degree in Robotics, Control, and Intelligent Systems from the Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland, in 2022. He is currently a postdoctoral researcher at LASA, EPFL. His primary research interests include human motor control, robotic grasping, and dexterous manipulation, with a particular emphasis on gaining a deeper understanding of human dexterity and leveraging system redundancy to enhance the dexterity of robotic systems.

Link: Google Scholar.

James Hermus

Biography. James Hermus received the B.S. degree in biomedical engineering from the University of Wisconsin-Madison, Madison, Wisconsin, USA, in 2016, and the M.S. and Ph.D. degrees in mechanical engineering from the Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, in 2018 and 2022, respectively. He recently started a postdoctoral research position at LASA, EPFL, Switzerland. His work investigates human (and robot) physical interaction. He is especially interested in research that will aid individuals with disabilities.

Link: Google Scholar.

Etienne Burdet

Biography. Etienne Burdet is Chair of Human Robotics at Imperial College London. He received two M.Sc. degrees in Mathematics and in Physics, and a Ph.D. in Robotics, all from ETH-Zurich, Switzerland. His main research interest is in human-machine interaction. He uses an integrative approach of neuroscience and robotics to investigate human sensorimotor control and to design efficient assistive devices and training systems for neuro-rehabilitation, which are tested in clinical trials and commercialized.

Link: Google Scholar.

Aude Billard

Biography. Aude Billard received the B.Sc. and M.Sc. degrees in physics from the Swiss Institute of Technology Lausanne (EPFL), Lausanne, Switzerland, in 1994 and 1995, respectively, and the Ph.D. degree in artificial intelligence from the University of Edinburgh, Edinburgh, U.K., in 1998. She is a Full Professor and the Head of the LASA Laboratory, School of Engineering, EPFL. Her research spans the fields of machine learning and robotics with a particular emphasis on learning from sparse data and performing fast and robust retrieval. Prof. Billard was the recipient of the IEEE-RAS Best Reviewer Award and IEEE-RAS Distinguished Service Award. Her research received the Best Paper Awards from the IEEE TRANSACTIONS ON ROBOTICS, RSS, ICRA, and IROS. She is the President-Elect of the IEEE Robotics and Automation Society (RAS) and a former IEEE RAS Vice-President of publication activities.

Link: Google Scholar.

Call for Abstracts

Our workshop will feature a poster session, and we welcome submissions of high-quality research contributions, including original research and preliminary findings. Submissions should include a 2-page abstract paper (PDF format – IEEE conference template, LaTex, two columns). All submissions will undergo peer review and will be evaluated based on their relevance and contribution to the workshop’s topics (listed below). Accepted submissions will be presented at the workshop through Poster Spotlight Talks (2-3 minutes presentation) and Poster Sessions and will be published on the workshop website, along with an optional 2-minute video summary.

Topics for submission:

  • Inverse Optimal Control
  • Inverse Reinforcement Learning
  • Acquisition of Skills
  • Multilimb Coordination
  • Interaction Control
  • Synergy
  • Paucity of Data


This part will be updated after the conference.


This workshop is supported by the Skill Acquisition in Humans and Robots (SAHR) project, European Research Council (ERC) Advanced Grant, project ID: 741945.