Insects and Hummingbirds: Mechanics, Control, and Bio-inspired Robots




The recent surge of interest in the development of micro air vehicles capable of hovering and fast maneuvering has led to several efforts to develop bio-inspired flapping wing robotic devices inspired by nature.  In fact, flying animals such as insects and hummingbirds demonstrate remarkable aerial maneuverability and stability, exceeding those of the conventional fixed or rotary wing aircraft in certain applications.  However, the underlying principles of their flight performance are far from being well understood.  In the bio-robotics lab, we investigate animal locomotion with the help of robotic devices, fluid experiments, and dynamics and control theories. Meanwhile, we apply the principles of animal locomotion to the development and control of bio-inspired robots capable of hovering and maneuvering in confined spaces.  In this talk I will highlight our recent findings on flapping flight including aerodynamics, dynamics and flight control of insect and hummingbirds during fast maneuvers, and the latest bio-inspired insect and hummingbird robots capable of hovering with high frequency flapping wings.


Xinyan Deng is an Associate Professor at the School of Mechanical Engineering at Purdue University. She received her B.S. degree from Tianjin University in Electrical Engineering and Automation, and her Ph.D. degree from the Department of Mechanical Engineering at the University of California at Berkeley. Her research interest is in the principles ofaerial and aquatic locomotion in animals and the development of bio-inspiredrobotic systems. Working in a highly interdisciplinary field, Dr. Deng collaborates with biologists and her work is published in diverse fields and journals suchas Science, Royal Society Interface,Journal of Experimental Biology, Experiments in Fluids, and IEEE Transactions on Robotics.  She received an NSF CAREER Award in 2006 on flying insect and robot research. She received the B.F.S. Schaefer Outstanding Faculty Scholar Award from Purdue University in 2015.  She served as the Co-Chair for theTechnical Committee on Bio-robotics of the IEEE Robotics and Automation Society from 2009-2013.  She has chaired andco-chaired varies NSF workshops, IEEE and ASME conference workshops and symposiums on bio-inspired robotics. Her research is funded by NSF, AFOSR, andAFRL, and as the PI she has received over $2.5M in federal research grants.

Minimum-cost Vessel Scheduling for Offshore Oil and Gas Projects 

Speaker: Dr Qun Lin, Senior Lecturer, Curtin University, Australia



Abstract: Scheduling support vessels is a critical issue in the offshore oil and gas industry. This talk introduces a mixed-integer linear programming model for designing an optimal vessel schedule to complete prescribed cargo delivery and off-take operations. The model involves various constraints including vessel capacity constraints, base opening hours, and facility commodity demands. For real problem instances, solving the proposed mixed-integer linear programming model is extremely challenging due to its massive dimension. We will discuss heuristic procedures for generating an initial feasible schedule; this schedule can then serve as a good starting point for commercial optimization software packages such as CPLEX. Our experience shows that providing a good starting point is essential for solving large-scale problem instances arising in practice. We have applied the proposed optimization model to investigate real vessel scheduling scenarios in the Australian North West Shelf Project.

About the Speaker: Dr Qun Lin was awarded a PhD in applied mathematics from Curtin University, Australia in June 2009. She then spent one year at the University of Melbourne as a postdoctoral research fellow, before returning to Curtin University in 2010. Dr Lin is currently a senior lecturer in the Department of Mathematics and Statistics at Curtin, where she teaches computational mathematics and actuarial science. Dr Lin’s research interests include granular materials, optimal control, numerical optimization, operations research, and the theory and applications of partial differential equations. She has published over 30 international journal papers in these areas, many in prestigious international journals such as Automatica, Journal of Optimization Theory and Applications, Physical Review E, and Journal of the Mechanics and Physics of Solids. Dr Lin has served as a guest editor for the Journal of Industrial and Management Optimization and has collaborated successfully with Woodside Energy Limited, Australia’s largest independent oil and gas company.

Ultimate precision limit for quantum parameter estimation



Abstract: Measurement and estimation of parameters are essential for science and engineering, where the main quest is to find out the highest achievable precision with given resources and design schemes to attain it. With recent development of technology, it is now possible to design measurement protocols utilizing quantum mechanical effects, such as entanglement, to attain far better precision than classical schemes. This has found wide applications in quantum phase estimation, quantum imaging, atomic clock synchronization, etc, and created a high demand for better understanding of measurement protocols based on quantum mechanical effects. In this talk I will present a general framework for quantum mechanical metrology which relates the ultimate precision limit to the underlying quantum dynamics. This framework provides efficient methods for computing the ultimate precision limit and optimal schemes to attain it. It also provides an analytical formula of the precision limit with arbitrary pure probe states, which spares the need of optimization required in previous studies. It is also shown that with noiseless dynamics a universal time scaling emerges as a fundamental property under the optimal scheme for quantum parameter estimation, this restores an intuition that has been recently questioned in the field, that time is always a valuable resource.

Biography: Haidong Yuan received the Bachelor’s degree from Tsinghua University and PhD from Harvard University. He then did his postdoctoral work at Massachusetts Institute of Technology.  From 2012 to 2014 he was an assistant professor at the department of Applied Mathematics, the Hong Kong Polytechnic University. Currently he is an assistant professor at the department of Mechanical and Automation Engineering, the Chinese University of Hong Kong.