Integrating Smart Materials and Solid Mechanics for Soft Robotics

Speaker: Wanliang Shan, Syracuse University

Abstract
Soft robotics offers a range of advantages over their conventional rigid counterparts, especially in cases where human-machine-environment interactions are involved. The design and fabrication of soft robotics puts high demand on the integration of smart materials and relevant mechanics into functional machines. This talk will first explore approaches to compliant robotic manipulation integrating existing smart materials and relevant solid mechanics, and then elaborate on the design and fabrication of new generation smart materials with tunable properties, as well as some examples of soft robotic mechanisms enabled by such novel smart materials and relevant mechanics. Future work on these topics will also be discussed.

Bio
Dr. Shan joined the Department of Mechanical and Aerospace Engineering at Syracuse University in July 2019. Before that, he was assistant professor of Mechanical Engineering at University of Nevada, Reno for five years, after finishing a two-year postdoctoral research fellowship at Mechanical Engineering Department at Carnegie Mellon University. He completed his Ph.D. study from Mechanical and Aerospace Engineering Department at Princeton University in 2012 and graduated with B.E. in Thermal Science and Energy Engineering from University of Science and Technology of China in 2006. His research group currently focuses on interdisciplinary research in Smart, Hybrid, Active and Nature-inspired Materials, Mechanics, and Machines. Fundamental insights from solid mechanics, materials engineering, machine learning, and thermal science are emphasized for the design and fabrication of soft multifunctional materials and high-performance robotic mechanisms, which impact critical application domains such as soft robotics and biomedical devices including wearables, for the ultimate goal of improving human-machine-environment interactions. His research, innovation and educational efforts have been funded by multiple NSF awards.