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About

Biography

Jonathan W. Hurst is a Professor of Robotics, co-founder of the Oregon State University Robotics Institute, and Chief Technology Officer and co-founder of Agility Robotics. He holds a B.S. in mechanical engineering and an M.S. and Ph.D. in robotics, all from Carnegie Mellon University.

His university research focuses on understanding the fundamental science and engineering best practices for legged locomotion. Investigations range from numerical studies and analysis of animal data, to simulation studies of theoretical models, to designing, constructing, and experimenting with legged robots for walking and running, and more recently, using machine learning techniques merged with more traditional control to enable highly dynamic gaits.

Agility Robotics is extending this research to commercial applications for robotic legged mobility, working towards a day when robots can go where people go, generate greater productivity across the economy, and improve quality of life for all.

He has been at Oregon State University since 2008.

Selected Publications

• Building Robots That Can Go Where We Go. Jonathan Hurst. IEEE Spectrum, February 2019.
• Walking and Running with Passive Compliance. Christian Hubicki, Andy Abate, Patrick Clary, Siavash Rezazadeh, Mikhail Jones, Andrew Peekema, Johnathan Van Why, Ryan Domres, Albert Wu, William Martin, Hartmut Geyer, and Jonathan Hurst
  IEEE Robotics and Automation Magazine, May 2018.
• Do Limit Cycles Matter in the Long Run? Stable Orbits and Sliding-Mass Dynamics Emerge in Task-Optimal Locomotion. Christian Hubicki, Mikhail Jones, Monica A. Daley, Jonathan W. Hurst. IEEE International Conference on Robotics and Automation (ICRA), May 2015.
• Don’t Break a Leg: Running Birds from Quail to Ostrich Prioritise Leg Safety and Economy on Uneven Terrain. Aleksandra V. Birn-Jeffery*, Christian M. Hubicki*, Yvonne Blum, Daniel Renjewski, Jonathan W. Hurst, Monica A. Daley . Journal of Experimental Biology, 217, 3786-3796.

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Research Interests

Hurst's research focuses on understanding the fundamental science and engineering best practices for legged locomotion. Investigations range from numerical studies and analysis of animal data, to simulation studies of theoretical models, to designing, constructing, and experimenting with legged robots for walking and running, and more recently, using machine learning techniques merged with more traditional control to enable highly dynamic gaits.

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