Integrating Smart Materials and Solid Mechanics for Soft Robotics

Date & Time: 
Fri, 04/05/2019 - 11:30am
Speaker: 
Wanliang Shan
Affiliation: 
University of Nevada, Reno
Location: 

Discovery Park F175

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 the soft robotic mechanisms enabled by such novel smart materials and relevant mechanics. Future work on these topics will also be discussed.

Wanliang Shan
Biography: 

Dr. Shan joined the Mechanical Engineering Department of University of Nevada, Reno (UNR) in 2014 after finishing a two-year postdoctoral research fellowship at Mechanical Engineering Department at Carnegie Mellon University. Before that, 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, biomedical devices, and wearable devices, for the ultimate goal of improving human-machine-environment interactions. His research, innovation and educational efforts have been funded by multiple NSF awards including one from National Robotics Initiative 2.0.

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