Abstract
With over half a billion years of evolutionary history, fishes swim with high efficiency, great agility, and surprising stealth in the three-dimensional aquatic environment. Therefore, it is undoubtedly natural for engineers to turn to fish as a source of new ideas on underwater propulsive systems. Over the past decades, roboticists, inspired by these biological systems, have constructed various fish-like robots that copy real fish morphology, locomotion, and movement. Recently, the direction of bio-inspiration has started to flip to bio-understanding—using robotics in engineering to help answer questions in biology. In this talk, I will first introduce how we construct and control the robotic fish following the paradigm of bio-inspiration. Then, I will give examples of applying real and virtual robots to help us explore why and how do fish school. Finally, I will briefly introduce my ongoing and future work in bio-inspiration and bio-understanding.
Biography
Liang Li is a Group Leader (PI) at the Max Planck Institute of Animal Behavior and the University of Konstanz. He received a bachelor’s degree in automation from Chongqing University in 2011 and a PhD in general mechanics and foundation of mechanics from Peking University in 2017. From February 2017 to June 2024, he was a Postdoctoral Research Fellow and Project Leader in the Department of Collective Behaviour, Max Planck Institute of Animal Behavior, Konstanz, Germany. His research interests include bio-inspired robots, swarm robots, collective behaviour in hybrid animal-robot systems, and bio-fluid dynamics in fish schools. He has published interdisciplinary studies in more than 46 peer-reviewed journals, including Science Robotics, Nature Communications, and PNAS, and also serves as a reviewer for these journals. He is an IEEE Senior Member, has received the Messmer Foundation Award and the Best Poster Award at the Conference on Robots for Science (organized by Science Robotics), and has secured multiple grants to pursue research into developing and applying robots for studying biological phenomena.