题目：Ratio of Hard-to-Soft Parts in Crawlers for Bio-inspired Robotics
时间：2025年5月30日 14:30-16:00
地点：龙宾楼 503会议室
邀请人：张文明 教授（振动、冲击、噪声研究所）
Biography
K. Jimmy Hsia is Professor in the School of Mechanical & Aerospace Engineering and School of Chemistry, Chemical Engineering & Biotechnolgy at Nanyang Technological University (NTU) in Singapore. He received Ph.D. from MIT. His research focuses on mechanics of soft materials and soft robotics, mechanobiology and bio-sensing, and smart adhesion. He is Fellow of AAAS, AIMBE, and ASME, and recipient of NSF Research Initiation Award, Max-Planck Society Scholarship, and Japan Society for Promotion of Science Fellowship. He was Founding Dean of Graduate College and Vice President (Alumni & International Affairs) at NTU, Vice Provost for International Programs at Carnegie Mellon University, and Founding Director of Nano and Bio Mechanics Program at NSF. He is Founding co-Editor-in-Chief of an Elsevier journal, Extreme Mechanics Letters.
Abstract
Hybrid robotics, integrating hard and soft components, combine the adaptability and contractility of the soft components with the control simplicity and load-bearing capacity of the rigid components to achieve versatile functionalities. This integrated approach is garnering increasing interest and inspiring numerous applications. Among these, robotic crawlers stand out as a prime example. Despite extensive research, determining the suitable balance between the hard and the soft parts in robotic crawlers for peak performance remains an open question. In this talk, I will present our recent work aiming at identifying the preferred hard-to-soft ratio and its influence on locomotion speed in crawlers by analyzing a wide range of natural crawlers across four motion mechanisms --- two-anchored (caterpillars), peristaltic (earthworms), undulatory (snakes), and multi-legged (centipedes and millipedes). Results show that the natural crawlers’ hard-to-soft ratios vary by mechanism. Comparison of the distinct clustering patterns in natural crawlers with that in bio-mimetic robotic crawling systems reveals that robotic crawlers are still far from being optimized and have not yet reached the potential of their natural counterparts. These results provide insights and guidance through the strategic integration of hard and soft components for future designs of bio-inspired robots, especially for crawling systems.
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