报告题目：Mechanical Models for studying legged locomotion and human balancing
报告人：Ambrus Zelei（匈牙利布达佩斯技术与经济大学应用力学系博士）
报告时间: 2019年9月9日（星期一）下午16:00-17:30
报告地点：明故宫校区18号楼705会议室
主办单位：国际合作处、机械结构力学及控制国家重点实验室、航空学院、校科协
报告摘要：
Mechanical models of different complexity are used for the dynamic analysis of human walking, hopping, running and human balancing. Most of these models incorporate some kind of controller, which plays the role of the human sensory, neural and motor system. These models are used for support the experimentally observed phenomena and for exploring the effect of parameter changes in an extended range.
One of our primary goals is to answer open questions related to optimal locomotion strategies, such as maximizing energy efficiency and minimizing injuries and muscle efforts. Our other ultimate goal is to find the balancing strategy which is used by the brain during standing still or during locomotion. The presentation summarizes the recent models, experiments and results.
报告人简介：
Ambrus ZELEI accomplished his Bachelor and Master of Sciences studies in the Faculty of Mechanical Engineering of Budapest University of Technology and Economics between 2002 and 2007. His specializations focused on solid mechanics and fluid mechanics. He spent on semester in the University of Bristol UK, where he finished his MSc thesis. In 2009, he received MSc degree in Techer of Engineering Sciences. He earned his PhD degree in 2015 in the Budapest University in the topic of control of underactuated multibody systems. From 2015 he is research associate at the Hungarian Academy of Sciences.
He has been contributing several research projects and industrial projects, such as
- MTA_BME Research Group on Dynamics of Machines and Vehicles,
- MTA-BME Lendület Human Balancing Research Group,
- Mechanical testing of Siemens electric aircraft battery units and instruments,
- Developement of the ACROBOTER service robot (European Union project).
From 2018 to 2022, he is the principal investigator of project titled as: ''Dynamics of human and artificial legged locomotion – running towards model-based predictions''.
