Southeast University, China
BIO: Dr. Bingjue Li received her B.S. degree from University of Science and Technology of China in 2011, and the M.S. and Ph.D. degree from University of Dayton in 2013 and 2017, respectively. She joined the Department of Mechanical Engineering at Southeast University as a lecturer in 2017. Her research interests include methodology of synthesizing shape-changing chains for applications including machine design and morphometric analysis, accurate estimation of the center of mass of branched systems, as well as developing other Fourier-based morphometric methods. Her work has been published in Scientific Reports, Journal of Mechanical Design, Journal of Mechanisms and Robotics, Evolutionary Biology, etc.
Speech Title: Mathematical and mechanical methods for morphometric analysis of 2D and 3D, open or closed outlines
Abstract: Morphometry is the field of multivariate statistical analysis of form variations as objects grow or evolve or vary within species. Morphometric methods are widely employed in biology, medicine, paleoanthropology, and many other applications. Common morphometric methods require analyzing a huge number of variables. Moreover, the results are sometimes difficult to interpret and evaluate. This presentation will introduce three novel morphometric methods for outline fitting and analysis. One is the dynamic circular epicycles method for 2D closed contours. The radii and phase angles of the epicycles can be used for analysis. Compared with elliptic Fourier analysis, it solves the problem of spurious rotation during normalization for curves with high bilateral symmetry. The second method is based on discrete cosine transform which can be used for 2D/3D open curves and surfaces. However, these two methods, like other Fourier-based morphometric methods, generate mathematical parameters from fitting functions that have no physical meaning for statistical analysis. Therefore, a method based on shape-changing chains, the same design idea that addresses shape-changing devices, is proposed. This method uses a set of segments with specific geometric properties to approximate 2D or 3D, open or closed curves. The kinematic parameters of the segments (such as the relative angle between segments, the length ratio of segments, or segment orientation, etc.) are used for statistical analysis. This method has the following advantages: the segmentation strategy is a flexible and automatic protocol that considers both biological and geometric features, a modest number of variables are used for statistical analysis, and the chain parameters have physical meanings. The validity and stability of the three methods have been verified by fitting and analyzing various biological samples. Several statistical analysis tools are used to analyze parameters obtained from fitting results of these methods, and the analysis results are compared with those of other morphometric methods. The results show that the three methods are effective and stable, and can be used as new morphometric methods.
Monash University, Australia
BIO: Elahe Abdi is a Lecturer at the Department of Mechanical and Aerospace Engineering, Monash University, Australia. She is the Director of Robotics in Medicine and Interaction Laboratory (RoMI Lab) and the Robotics Education Liaison Representative at the Australian Robotics and Automation Association.
Dr Abdi received the PhD degree in Robotics in 2017, from EPFL, Switzerland. She then moved to Australia to establish her research team active in human-robot interaction with application in medicine, construction and service robotics. Elahe has received numerous recognitions including Finalist for the Women’s Agenda Award “Emerging Leader in STEM” in 2021. Her research interests include human-robot interaction, shared autonomy, and haptics.
Speech Title: Shared autonomy in human-robot collaboration
Abstract: Shortage of professional workforce is a significant challenge in Australia and across the world, partially due to an ageing population. This is pronounced in a wide range of industries including healthcare, construction, agriculture, education, and tourism, among others. It can translate into reduced quality and less efficiency in processes and services as well as excessive working hours for the available workforce.
Drawing on humans’ superior decision-making capabilities and robots’ edge in conducting precise and repetitive tasks, human-robot collaboration provides a viable solution to the scarcity in the labour market. In this talk, the concept of shared autonomy in human-robot collaboration will be discussed with examples from two unpredictable and unstructured environments in surgery and construction. The role of intuitive human-robot interfaces, perception, and artificial intelligence for a successful shared autonomy framework in laparoscopic surgery and installing façades in high-rise buildings will be discussed. The talk will conclude by highlighting some of the challenges in human-robot collaboration and suggestions for future work.