Lockheed Martin Robotics Seminar: Chen Li, "Terradynamics of Animal and Robot Locomotion"
Friday, November 11, 2016
2121 JM Patterson
301 405 4358
Lockheed Martin Robotics Seminar
Terradynamics of Animal and Robot Locomotion in Complex Terrains
Department of Mechanical Engineering
John Hopkins Whiting School of Engineering
Aero- and hydrodynamics that describe fluid-structure interactions have helped us understand how animals fly and swim and develop aerial and aquatic vehicles that move through air and water rapidly and efficiently. By contrast, we know surprisingly little about how terrestrial animals move so well in natural terrains like deserts and forests, and even the best of our robots still struggle in complex terrains like building rubble or loose Martian soil. My research aims to create the new field of terradynamics that describe complex locomotor-terrain interactions to better understand animal locomotion and improve robot locomotion in complex terrains.
In this talk, I will demonstrate that, despite the formidable diversity and complexity of natural and artificial terrains, terradynamics can be created by integrating biomechanics, bio-inspired robotics, and contact mechanics/dynamics studies and developing new experimental tools and theoretical models. First, I will briefly review my previous research on creating the first terradynamics of legged locomotion on “flowable” ground such as sand and Martian soil, which enabled quantitative prediction of forces and movement and provided design and control principles for legged robots. Then, I will discuss on my recent research that begins to expand terradynamics into complex 3-D terrains such as dense vegetation and cluttered building rubble, where I discovered the first terradynamic shapes that help animals and robots traverse cluttered obstacles, analogous to airfoil and streamlined shapes that facilitate movement in fluids. Finally, I will posit my vision to create new terradynamics of complex 3-D terrains by developing “locomotion energy landscapes” to statistically predict movement.
Chen Li is an Assistant Professor in the Department of Mechanical Engineering, Johns Hopkins University, and affiliated with JHU’s Laboratory for Computational Sensing & Robotics (LCSR). Before joining JHU in 2016, Dr. Li was a Miller Postdoctoral Fellow at UC Berkeley from 2012 to 2015 and earned his PhD degree in Physics from Georgia Tech in 2011 Dr. Li received a Career Award at the Scientific Interface from Burroughs Wellcome Fund, a Miller Research Fellowship from UC Berkeley’s Miller Institute for Basic Research in Science, and a Sigma Xi Best PhD Thesis Award from Georgia Tech. His research over the last few years has resulted in two highlight papers (Bioinspiration & Biomimetics 2015, IROS 2016) and two best student papers (SICB 2009, RSS 2012). He has been a collaborator in the Army Research Lab Micro Autonomous Systems and Technology CTA since 2009.