MEchanics GAthering -MEGA- Seminar: Fluid physics driven bio-inspired robots
Event details
| Date | 18.11.2021 |
| Hour | 16:15 › 17:30 |
| Speaker | Qiang Zhong (Fluid Systems Lab, University of Virginia) |
| Location | Online |
| Category | Conferences - Seminars |
| Event Language | English |
Abstract Exploring, monitoring, and using oceans in a smart and sustainable way is an extreme challenge to current marine technologies. One of the solutions could lie in autonomous marine robotic systems. Successful autonomous robots must operate in complex and unstructured offshore environments, so they should be ‘intelligent’- to accomplish missions autonomously and efficiently. Bio-inspired engineering is a popular way to endow autonomous robots with high-performance, which requires three areas of expertise: flow physics, robot design, and control. However, one of the critical challenges could be the difficulties of transferring knowledge between the three classic research areas, therefore limiting the bio-inspired studies. In this talk, we will present our recent effort that combines these three approaches to uncover one of the secrets of high-performance swimming: what is the ‘best’ stiffness of a swimming fish-like robot? We first gained inspiration from real tuna tails by measuring tail stiffness responses, then developed a reduced-order theoretical tuna model coupled with an aerodynamic model to explore the role of stiffness from a reduced-order modeling aspect. Furthermore, our understanding of biomechanics, fluid dynamics, and elastic theory helped us design a bio-inspired robot tuna. Coupled with our cyber-physical water tunnel rig, we explored the role of stiffness in real free-swimming conditions. Comparing results from experiments and modeling, we found that the ‘best’ stiffness should scale with swimming speed squared to maintain maximum swimming performance. The proposed tunable stiffness strategy was proven effective on the robotic fish with significant efficiency enhancement in real swimming missions, which overcame the long-existing performance bottleneck of soft-structured bio-inspired fish robots and provided deeper insights into fish swimming.
Bio Qiang Zhong is currently a Postdoctoral Researcher at the Department of Mechanical and Aerospace Engineering, University of Virginia, USA. He received his Ph.D. in Mechanical Engineering from the University of Virginia in 2021, his master's degree in Mechanical Engineering from the University of Pittsburgh in 2016, and his bachelor’s degree in Biosystem Engineering from Zhejiang University in 2014. His research interests include developing physically intelligent robots with a combination of fluid mechanics, robot design, and control for ocean explorations. He has published a series of high-quality journals, including Science Robotics, Journal of Fluid Mechanics, etc. He is the co-founder of the Intelligent and Bio-inspired Mechanics Seminar (IBiM) series.
Bio Qiang Zhong is currently a Postdoctoral Researcher at the Department of Mechanical and Aerospace Engineering, University of Virginia, USA. He received his Ph.D. in Mechanical Engineering from the University of Virginia in 2021, his master's degree in Mechanical Engineering from the University of Pittsburgh in 2016, and his bachelor’s degree in Biosystem Engineering from Zhejiang University in 2014. His research interests include developing physically intelligent robots with a combination of fluid mechanics, robot design, and control for ocean explorations. He has published a series of high-quality journals, including Science Robotics, Journal of Fluid Mechanics, etc. He is the co-founder of the Intelligent and Bio-inspired Mechanics Seminar (IBiM) series.
Practical information
- General public
- Free
Organizer
- MEGA.Seminar Organizing Committee