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Provided by ASME Logo The American Society of Mechanical Engineers
IDETC-CIE 2021
Online, Virtual

Virtual Conference: August 17 – 19, 2021

Keynotes & Special Sessions

 

Peter Wright

Keynote Speaker: Peter Wright, Independent Motorsport Consultant

Keynote Title: Half a Century in Motorsport: From Speed to Safety

Abstract: From an early interest in motorsport the 1950's, Peter Wright joined the Grand Prix team, British Racing Motors (BRM) in 1967 at the age of 21 years. In a career spanning over half a century, he has experienced the golden age of Formula 1 technical development. After 21 years with the Lotus Group, including the roles of Technical Director of Team Lotus, Managing Director of Lotus Engineering, and a Director of Group Lotus, his career spanned the eras of the aerodynamic development of racing cars, including the development of Ground Effect and Active Suspension, during which he worked with and formed a lasting friendship with Bill Milliken.

In 1994, following the death of Ayrton Senna, Wright joined the international motorsport sanctioning body, the FIA as Technical Adviser, working on motorsport regulation, motorsport safety R&D, and road car safety. In 25 years with the FIA, projects included the introduction of Accident Data Recorders, the development of HANS, flying Le Mans sports cars, High Speed Barriers, Advanced Frontal Protection (Halo),the prevention of spinal injuries in frontal impacts, and research into motorsport concussion, as well as the development of a Balance of Performance system for GT cars, and the F1 hybrid powertrain regulations. As President of the FIA Safety Commission, he was responsible for introducing numerous safety regulations, and chaired the Jules Bianchi accident investigation.

Today, nearly retired, he is responsible for the drawing up of Sporting and Technical Regulations for the recently launched eSkootr Championship.

Biography

Peter Wright was educated at the Wellington College and later Trinity College, Cambridge, where he graduated with an MA in Mechanical Sciences. In 1967, he was recruited by F1 team British Racing Motors (BRM), where he was an aerodynamicist and vehicle development engineer. In 1969, he went to work for Specialised Mouldings Ltd., which designed and manufactured racing car bodies. He designed and ran Specialised Mouldings’ quarter-scale motorsport wind tunnel.

In 1974, Wright became General Manager of Technocraft, a company owned by Colin Chapman, the founder of Lotus. He was responsible for the F1 Team Lotus wind tunnel programme which led to the development of the first ground effect car, the Lotus 78. The car was an instant success and its successor, the Lotus 79, went on to the win the 1978 Formula One World Championship. Wright later became director of Research and Development at Team Lotus and was responsible for the development of the Lotus T78, 79, 80, 81, 86, 87, 88, 91, 92 and 93 Formula One cars. In 1983, he became responsible for Active Suspension development in Lotus Engineering, and in 1987 for the development of Active Suspension on the Lotus F1 car. In 1988, he became Managing Director of Lotus Engineering, responsible for over 600 staff.

The following year, he was appointed a Director of Group Lotus and would later go back to the track as Technical Director of Team Lotus from 1991 to 1994. With a vast amount of experience in motor sport, Wright was asked to be a technical adviser for the FIA in 1995, from which he retired in 2020. He worked across a number of FIA affiliated organisations including the FIA Foundation and the FIA Institute for Motor Sport Safety. He was President of the FIA GT and Sportscar Commissions, the FIA Safety Commission, and the FIA Environmentally Sustainable Motor Sport Commission. He served as a Director of EuroNCAP, a Member of the EuroNCAP Technical Committee, a Member of the PNCAP Technical Committee and a technical adviser on EU safety, emissions, and traffic legislation.

 

 

Dr. Raju Mattikalli

Keynote Speaker: Dr. Raju Mattikalli, Boeing Research & Technology

Keynote Title: Design of Networked Systems

Abstract: Data is revolutionizing how physical systems operate. To enable data gathering and processing, computers and sensors are increasingly being built into appliances, homes, cars, airplanes and factories. Algorithmic design of such cyber-physical systems needs to address the integration of sensing, computational and communication sub-systems into the physical design. In the aerospace industry, we have unique challenges associated with the design of such networked systems arising from their scale and complexity. In this talk I will highlight some design challenges and will describe algorithmic solutions as it applies to aerospace products including airplanes, real-time avionics and perimeter defense systems.

Biography

Dr. Raju Mattikalli is a Technical Fellow in Applied Mathematics, Boeing Research & Technology. Mattikalli has over 33 years of experience conducting R&D in the area of Computational Design and Manufacture Planning. His area of expertise is System Level Design, Mathematical Modeling, Optimization, Geometric Modeling, Networked Systems and Robotics.

Dr. Mattikalli has led efforts for optimal sensor positioning along the US-Mexico border, for Functional Integration on the 787, and for system level design and optimization of avionics and electrical systems. At Terabeam, a free-space optical networking startup, Mattikalli developed network design and optimization tools. Mattikalli was co-PI on DARPA’s META program on new system engineering methods.

Dr. Mattikalli has a Ph.D. in Mechanical Engineering from Carnegie Mellon University. He has authored several journal and conference papers and has 7 patents. He served as an Associate Editor for the IEEE Trans. on Automation Science and Engineering from 2007-2008. He has served on several proposal review committees and was a reviewer for numerous journal and conference papers. In 2008, he received the Boeing Phantom Works breakthrough technology award. He currently serves as an Associate Editor for ASTM Journal for Smart and Sustainable Manufacturing Systems.

 

 

The digitalization of enterprises and creation of model-based enterprises has become a priority among industry and government leaders. In the broadest sense, a model-based enterprise refers to creating a fully digital “system-of-systems” model that serves as the authoritative information source for all activities, organizations, and assets across an enterprise. Digital engineering is a core functional component of such a digital enterprise.

While the concept of a digital enterprise and digital engineering attracts attention with the vision of real-time information transparency, both the investment and risk of failure is high. Organizations understand the value of having relevant product data at their fingertips when making high level decisions but have struggled in implementing solutions across all levels of an enterprise. However, at separate levels, designers and engineers have achieved great successes through the adoption of digital technologies such as CAD, CAM, CAE, and technical data management software.

Aided by emerging technologies such as internet-of-things, 3D printing, augmented reality, virtual reality, digital twins, and artificial intelligence, one would expect that the benefits of digitalization are scalable across levels of digital enterprises. Towards a more holistic organizational adoption of digitalization technologies, key questions remain about the costs, risks, appropriate focus, appropriate scale, change management, how to get started, return-on-investment, and time required to recoup the investment and gain benefit. Indeed, even the metrics to measure benefits are topics to explore.

In this panel we will hear from industry experts in the oil and gas, aerospace, and automotive industries about how digitalization and model-based enterprise has been implemented in their organizations. We will hear about the strategies that have been most successful in implementing these technologies, and where they still find challenges remain. Industry participants will gain insight on how to make the business case for digital engineering, mitigating the risks of such initiatives, and how to get started. Academic attendees will gain insight into topical areas for research and teaching.

Moderators:

Paul Witherell

Paul Witherell
CIE

Kieran Kavanagh

Kieran Kavanagh
Digitalization

 

Panelists:

Marc Halpern

Marc Halpern
VP Analyst
Gartner

Michael Grieves

Michael Grieves
FIT

Raju S. Mattikalli

Raju S. Mattikalli
Boeing Research & Technology

David Cheng

David Cheng
Fluor

Yan Fu

Yan Fu
Ford

Biographies

Marc Halpern, Gartner, (Overview/ General)
Marc Halpern, P.E., Ph.D., is a VP Analyst at Gartner and focuses on design, engineering and product life cycle management strategies and software applications in the manufacturing verticals unit. His coverage spans software applications and best practices for discrete manufacturing. Discrete manufacturing industries served include aerospace, automotive, industrial, durable consumer goods, medical devices and industrial equipment. He also covers building information modeling and digital twins

Michael Grieves, FIT, (Background/ Digital Twin)
Dr. Michael Grieves is an internationally renowned expert in Product Lifecycle Management (PLM) and originated the concept of the Digital Twin. His focus is on virtual product development, engineering, systems engineering and complex systems, manufacturing, especially additive manufacturing, and operational sustainment. Dr. Grieves has written the seminal books on PLM and seminal chapters on Digital Twins. In addition to his academic credentials, Dr. Grieves has over four decades of extensive executive and deep technical experience in both global and entrepreneurial technology and manufacturing companies.

Raju S. Mattikalli, Boeing, (Aerospace)
Dr. Raju Mattikalli is a Technical Fellow in Applied Mathematics, Boeing Research & Technology. Mattikalli has over 33 years of experience conducting R&D in the area of Computational Design and Manufacture Planning. His area of expertise is System Level Design, Mathematical Modeling, Optimization, Geometric Modeling, Networked Systems and Robotics.

David Cheng, Fluor, (Oil and Gas)
David Cheng, PhD, PE is a Technical Director and Fluor Fellow with the Fluor Corporation. David has more than 25 years of experience in pipeline network planning, system hydraulics, flow assurance and pipeline engineering. David has diverse international and domestic project experiences, direct and in-depth experience in single phase and multiphase pipeline hydraulics and flow assurance modeling for upstream and midstream oil and gas pipeline systems.

Dr. Yan Fu, Ford, (Automotive)
Dr. Yan Fu is Manager and Technical Leader of Business Strategy and Engineering Optimization, and she is leading the Product Development and Strategy Analytics Group at Ford Global Data, Insight & Analytics (GDIA). Dr. Fu and her team are currently developing sophisticated business analytics, optimization and other strategic decision support tools to support business decision making, vehicle and powertrain design optimization and robustness, fuel economy strategy, and safety initiatives. Dr. Fu is a SAE Fellow and an ASME Fellow.

 

 

Generative Design: Succeed or Fail in Product Development

Abstract: Generative design is a computational approach for synthesizing complex geometric forms of products at different scales using techniques including evolutionary algorithms, rule-based design, knowledge-based engineering, machine learning, etc. This design methodology is attractive because it can explore innumerable possible permutations of a solution to find the best option. The diversity of designs is high, which can even result in a new design that people may have not seen or thought of before. However, having too many options could also be a bad thing, especially if you have the fear of making decisions. In addition, generative design may require the designers to create the algorithm that generates the plans and to follow the linear design process: briefing, ideation, and deciding, but these are not how designers work or how designs get done inside design firms. This panel session serves as a platform to discuss the practical issues of generative design and stimulate us to think about how to apply generative design in the future of product development.

Panelists:

  • Dr. Charlie C.L. Wang, Professor at The University of Manchester
  • Dr. Timothy W. Simpson, Professor at The Pennsylvania State University
  • Mr. Blake Courter, CTO at nTopology
  • Dr. Hyunmin Cheong, Principal Research Scientist at Autodesk Research

 

 

Moderator: Christopher McComb, Special Sessions Chair, DAC Executive Committee

Panelists:

Sandeep Neema

Sandeep Neema
Program Manager, Information Innovation Office, Defense Advanced Research Projects Agency

Conrad Tucker

Conrad Tucker
Professor, Department of Mechanical Engineering, Carnegie Mellon University

Anita Woolley

Anita Woolley
Associate Professor, Tepper School of Business, Carnegie Mellon University

Emrah Bayrak

Emrah Bayrak
Assistant Professor, School of Systems and Enterprises, Stevens Institute of Technology

Biographies

Sandeep Neema, Program Manager, Information Innovation Office, Defense Advanced Research Projects Agency
Dr. Sandeep Neema joined DARPA in July 2016 and again in September 2020. His research interests include cyber physical systems, model-based design methodologies, distributed real-time systems, and mobile software technologies. Prior to joining DARPA, Dr. Neema was a professor of electrical engineering and computer science at Vanderbilt University. Dr. Neema participated in numerous DARPA initiatives through his career including the Transformative Apps, Adaptive Vehicle Make, and Model-based Integration of Embedded Systems programs. Dr. Neema has authored and co-authored more than 100 peer-reviewed conference, journal publications, and book chapters. Dr. Neema holds a doctorate in electrical engineering and computer science from Vanderbilt University, and a master’s in electrical engineering from Utah State University. He earned a bachelor of technology degree in electrical engineering from the Indian Institute of Technology, New Delhi, India.

Conrad Tucker, Professor, Department of Mechanical Engineering, Carnegie Mellon University
Conrad Tucker is an Arthur Hamerschlag Career Development Professor of Mechanical Engineering and holds courtesy faculty appointments in machine learning, robotics, and biomedical engineering at Carnegie Mellon University. His research focuses on the design and optimization of systems through the acquisition, integration, and mining of large scale, disparate data. Tucker has served as PI/Co-PI on federally/non-federally funded grants from the National Science Foundation (NSF), the Air Force Office of Scientific Research (AFOSR), the Defense Advanced Research Projects Agency (DARPA), the Army Research Laboratory (ARL), the Office of Naval Research (ONR) via the NSF Center for eDesign, and the Bill and Melinda Gates Foundation (BMGF). In February 2016, he was invited by National Academy of Engineering (NAE) President Dr. Dan Mote, to serve as a member of the Advisory Committee for the NAE Frontiers of Engineering Education (FOEE) Symposium. He received his Ph.D., M.S. (Industrial Engineering), and MBA degrees from the University of Illinois at Urbana-Champaign, and his B.S. in Mechanical Engineering from Rose-Hulman Institute of Technology.

Anita Woolley, Associate Professor, Tepper School of Business, Carnegie Mellon University
Anita Williams Woolley is an Associate Professor of Organizational Behavior and Theory at Carnegie Mellon University's Tepper School of Business. She has a PhD in Organizational Behavior from Harvard University, where she also earned Bachelor's and Master’s degrees. At the Tepper School of Business, she teaches MBA and executive education courses on managing people and teams in organizations. Prof. Woolley's research includes seminal work on team collective intelligence, which was first published in Science in 2010 and has been featured in over 3000 publications and media outlets since, including Forbes Magazine, the New York Times, and multiple appearances on NPR. Professor Woolley's research has been published in Science, Proceedings of the National Academy of Sciences, Academy of Management Review, Organization Science and Social Neuroscience, among others. Her research has been funded by grants from the National Science Foundation, the U.S. Army Research Institute, DARPA, as well as private corporations. She has won awards for her research and her teaching.

A. Emrah Bayrak, Assistant Professor, School of Systems and Enterprises, Stevens Institute of Technology
A. Emrah Bayrak is an Assistant Professor in the School of Systems and Enterprises at Stevens Institute of Technology. He received his B.S. degree (2011) in mechatronics engineering from Sabanci University, M.S. (2013) and PhD degrees (2015) in mechanical engineering from the University of Michigan. He worked as a post-doctoral research fellow in the Optimal Design Lab at the University of Michigan, and as a Research Scientist in the Integrated Design Innovation Group at Carnegie Mellon University. Dr. Bayrak’s research focuses on integrating computational methods with human cognition for the design and control of smart products and systems. He is particularly interested in developing artificial intelligence (AI) systems that can effectively collaborate with humans considering unique capabilities of humans and computational systems. He studies the impact of AI behaviors, division of labor and coordination on trust and performance in human-AI collaboration. His research uses methods from design, controls and machine learning as well as human-subject experiments on virtual environments such as video games.

Alison Olechowski, Assistant Professor, Department of Mechanical & Industrial Engineering, University of Toronto
Alison Olechowski is an Assistant Professor in the Department of Mechanical & Industrial Engineering at the University of Toronto. Dr. Olechowski and her team study collaborative engineering design work. In particular, her lab is investigating modern collaborative CAD software, with the aim of uncovering new and effective ways to design. Dr. Olechowski completed her PhD at the Massachusetts Institute of Technology (MIT) studying product development decision-making during complex industry projects. Dr. Olechowski completed her BSc (Engineering) at Queen’s University and her MS at MIT, both in Mechanical Engineering. She has studied engineering products and projects in the automotive, electronics, aerospace, medical device and oil & gas industries.

Daniel Selva, Assistant Professor, Department of Aerospace Engineering, Texas A&M University
Daniel Selva is an Assistant Professor of Aerospace Engineering at Texas A&M University, where he directs the Systems Engineering, Architecture, and Knowledge (SEAK) Lab. His research interests focus on artificial intelligence and human-machine collaboration for early design and architecting of complex engineered systems, with a strong focus on space systems. Dr. Selva holds dual degrees in electrical engineering and aerospace engineering from Universitat Politecnica de Catalunya (Spain) and Supaero (France), and a PhD in Space Systems Engineering from MIT. Before doing his PhD, Dr. Selva worked for 4 years in Kourou (French Guiana) as an avionics specialist within the Ariane 5 Launch team. Dr. Selva has co-authored over 70 peer-reviewed publications, including several best paper awards. Dr. Selva is a member of the European Space Agency's Advisory Committee for Earth Observation and the Secretary of the AIAA Intelligent Systems Technical Committee.

 

Nabil Z. Nasr

Nabil Z. Nasr, Ph.D.

Associate Provost for Academic Affairs
Director, Golisano Institute for Sustainability
Rochester Institute of Technology
CEO, REMADE Institute
Rochester, New York

Title: Innovation in Reducing Embodied Energy and Decreasing Emission through Circular Economy

Abstract: In response to growing challenges of expanding energy consumption and emissions in manufacturing there is a need to develop a strategy at the national level with clear goals and objectives to address those challenges. In 2017 the REMADE Institute was formed as a public/private partnership focused on developing transformational technologies to accelerate the transition to a Circular Economy for plastics, metals, fibers and e-waste. The institute is funded through a cooperative agreement with the Department of Energy with $70 Million in Federal funding and $70 Million in private funding for the first 5 years. This presentation will provide an overview of the REMADE Institute and its objectives and technology strategy. REMADE seeks to enable early stage applied research and development of key industrial platform technologies that could dramatically reduce the embodied energy, emissions, and waste and increase material availability associated with industrial-scale materials production and processing. Eliminate and/or mitigate technical and economic barriers that prevent greater material recycling, recovery, remanufacturing, & reuse.

Biography: Dr. Nabil Nasr is Associate Provost for Academic Affairs and Director of Golisano Institute for Sustainability at Rochester Institute of Technology (RIT). He also founded RIT’s Center for Remanufacturing and Resource Recovery, a leading source of applied research and solutions in remanufacturing technologies. Dr. Nasr’s research interests focus on remanufacturing, circular economy, life cycle engineering, cleaner production and sustainable product development, and he is considered an international leader in research and development efforts in those disciplines. Nasr is also the founding Chief Executive Officer of the REMADE Institute, providing oversight of node-level research roadmap development as well as corporate engagement of the Institute’s largest industrial partners. This national coalition is working on new clean energy initiatives, focusing on driving down the cost of technologies essential to reuse, recycle and remanufacture materials such as metals, fibers, polymers and electronic waste. Dr. Nasr currently serves as a member of the International Resource Panel of the United Nations Environment Programme (UNEP). In addition, he has been an expert delegate with the U.S. Government in several international forums such as the Asia Pacific Economic Cooperation (APEC), United Nations, World Trade Organization, and the OECD. He holds an MS and PhD in Industrial & Systems Engineering from Rutgers University.

Please join us for an interactive DFMLC panel discussion with several past Kos-Ishii Award Winners. In this discussion, we will reflect on the contributions made by the DFMLC research community to advancing design and manufacturing over the past decade as well as envisioning the future role of the DFMLC community over the coming decade and its relationship with other ASME and external communities.

Additional information forthcoming

Shane Xie

Shane Xie

University of Leeds

Title: Innovative Robotic Technology for the Future of Healthcare

Abstract: Stroke and neurological diseases have significant impact on our society, this talk will discuss the key societal challenges, robotic technologies for delivering effective care and opportunities for the healthcare industry. The keynote will cover the recent development of robotics for stroke rehabilitation, the research gaps and the need for new technologies in neuroscience, robotics and artificial intelligence. The talk will introduce a EPSRC-funded project on intelligent reconfigurable exoskeletons tailored to meet patients’ needs, deliver effective diagnosis and personalised treatment, and monitored remotely by rehabilitation therapists. The talk will also briefly introduce the Leeds Centre for Assistive/Rehabilitation Robotics and our work on ankle robot, gait exoskeleton, gait upper limb bilaterial robot, neuromuscular and brain computer interfaces. The focus is on the enabling technologies for those whose strength and coordination have been affected by amputation, stroke, spinal cord injury, cerebral palsy and ageing.

Biography: Prof Shane (Sheng Q) Xie, Ph.D., FIPENZ, is the Chair of Robotics and Autonomous Systems and Director of the Rehabilitation Robotics Lab at the University of Leeds, and he was the Director of the Rehabilitation and Medical Robotics Centre at the University of Auckland, New Zealand (NZ, 2002-2016). He has >28 years of research experience in healthcare robotics and exoskeletons. He has published > 400 refereed papers and 8 books in rehabilitation exoskeleton design and control, neuromuscular modelling, and advanced human-robot interaction. He has supervised >15 postdocs, 62 PhDs and 80 MEs in his team with funding of >£27M from five countries since 2003. His team has invented three award-winning rehabilitation exoskeletons. He is an expert in control of exoskeletons, i.e. impedance control, adaptive control, sliding mode control, and iterative learning control strategies. He has received many distinguished awards including the David Bensted Fellowship Award and the AMP Invention Award. He is an elected Fellow of the Institute of Professional Engineers of New Zealand and the Technical Editor for IEEE/ASME Transaction on Mechatronics.

Mohammad Younis

Mohammad I. Younis

Physical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
Department of Mechanical Engineering, State University of New York at Binghamton, Binghamton, NY, USA

Title: Dynamic-Based Micro and Nano Devices and Phenomena

Abstract: Miniature structures and devices have captured the attention of the scientific community for several decades for their unprecedented attractive features. Today, several micro-electro-mechanical systems MEMS devices are being used in our everyday life, ranging from accelerometers and pressure sensors in automobiles, radio-frequency (RF) switches and microphones in cell phones, and inertia sensors in video games. Due to the quest to boost sensitivity, reduce power consumption, and increase integration density, the past two decades have witnessed the emergence of Nano-electro-mechanical systems NEMS. With the increasing demand to embed more intelligence into various applications, MEMS and NEMS continue to play key role on advancing innovation.

Along with their great promise, micro and nano devices have brought new challenges and a wide spectrum of unexplained and less-understandable mechanical behaviors and phenomena. Because these devices employ moveable compliant structures and due to the interaction with short-range forces, many of these challenges are related to their dynamical behavior, which is mostly nonlinear.

In this talk, we demonstrate that by developing a proper understanding and deep insight into the dynamics and nonlinear mechanics phenomena at the micro and nano scale, new technological solutions and innovative ideas can be realized leading to new generations of superior devices. The talk will overview some of the recent revealed intriguing phenomena at the micro and nano scale including internal resonances and modes veering. Then, we discuss the realization of smart resonant sensing platforms utilizing multi-modal vibration excitation of structures to achieve multiple functionalities. These include boosting sensitivity, compensating for temperature drift, and combining sensing and actuation on a single device. In one application, active switches triggered by the detection of gas will be demonstrated. Then we discuss the static and dynamic behavior of actively tunable structures; which can be tuned using electrostatic and or/electrothermal actuation. We will discuss the potential of implementing such structures for logic, memory, and filtering applications. The talk will end on future directions andperspectives.

Biography: Mohammad I. Younis received a Ph.D. degree in engineering mechanics from Virginia Polytechnic Institute and State University, Blacksburg, VA, in 2004. From 2004-2013 he served as an assistant and then as an associate professor of Mechanical Engineering at the State University of New York (SUNY), Binghamton, NY. In 2013, he moved to King Abdullah University of Science and Technology, Saudi Arabia, where he served as an associate and then full professor of Mechanical Engineering and a Director of the MEMS and NEMS Characterization and Motion Laboratory. Dr. Younis is a recipient of the SUNY Chancellor’s Award for Excellence in Scholarship and Creative Activities in 2012, the National Science Foundation Faculty Early Career Development Award in 2009, and the Paul E. Torgersen Graduate Research Excellence Award in 2002. He holds several U.S. patents in MEMS sensors and actuators. He serves as an Associate Editor of Nonlinear Dynamics, Journal of Computational and Nonlinear Dynamics, Journal of Vibration and Control, and Meccanica. He is a member of the American Society of Mechanical Engineers ASME and IEEE.

Marcia O'Malley

Marcia K. O'Malley, Ph.D.

Thomas Michael Panos Family Professor in Mechanical Engineering,
Computer Science,
and Electrical and Computer Engineering
Rice University
Houston TX USA

Title: Designing wearable robots for physical human-robot interaction

Abstract: Robots are increasingly transitioning from factories to human environments: today we use robots in healthcare, households, and social settings. I'm particularly interested in the potential for improving human performance with wearable robotic devices. Physical interactions between robots and humans offer an opportunity for the human and robot to implicitly communicate. For example, a rehabilitation robot exoskeleton can guide and train human movements, or a wearable haptic device can be used to convey informative tactile cues to the user. As engineers, we must consider the unique design and control constraints that are introduced when we design robots that are to be worn by the human, such as the complex degrees of freedom of human joints, the limitations of our human perceptual capabilities, and the necessity for compliant control algorithms to ensure user safety. This talk will feature recent research from my lab and will highlight these design challenges and the unique approaches that we have taken to ensure that the wearable robot and human achieve more together than either can achieve alone.

Biography: Marcia O'Malley is the Thomas Michael Panos Family Professor in Mechanical Engineering, Computer Science, and Electrical and Computer Engineering at Rice University where she directs the MAHI (Mechatronics and Haptic Interfaces) Lab. She received her BS in Mechanical Engineering from Purdue University, and her MS and PhD in Mechanical Engineering from Vanderbilt University. Her research is in the areas of haptics and robotic rehabilitation, with a focus on the design and control of wearable robotic devices for training and rehabilitation. She has won awards for exemplary teaching at Rice, and she was the recipient of both an ONR Young Investigator Award and an NSF CAREER Award. She is a Fellow of both the ASME and the IEEE. Her editorial roles include Associate Editor-in-Chief for the IEEE Transactions and Senior Editor for the ACM Transactions on Human Robot Interaction. She is the incoming chair of the IEEE Robotics & Automation Society Conference Editorial Board.

Friedrich Pfeiffer

Friedrich Pfeiffer

Institute of Applied Mechanics
Department of Mechanical Engineering
Technical University Munich

Title: Steps towards non-smooth multibody dynamics

Abstract: Multibody dynamics theories including non-smooth effects came up not before the second half of the last century. In my previous Institute we had quite a number of industry problems requiring urgently new solution ideas, for example gear rattling, turbine blade dampers, roller coasters and automotive drive trains, all with contact problems influencing dynamics, for some cases dominating it.

We started, as many other colleagues working in the field, with a description of such problems applying time-varying sets of equations of motion due to the fact, that contact, events like impacts or friction reduce the number of degrees of freedom of the system as long as the contact is active, and generate additional degrees of freedom when contacts are passive and open. This works for small systems, but fails for larger ones. Introducing the complementarity idea solved this problem, but generated new numerical ones. They were avoided by an idea of Alart, Curnier (1991), replacing complementarity by a set theoretical method, the prox-functions. Including these advancements into multibody system theory made successful treatment of large dynamical systems possible.

The lecture will focus on evolution of the theoretical fundament and on typical industry applications, typical also for the author’s academic life during the last decades.

Biography: After Diploma (Dipl.-Ing.) in mechanical engineering and dissertation in aerodynamics (Dr.-Ing.) at the Technical University Darmstadt, Germany, Friedrich Pfeiffer went to the German aerospace industry, today EADS, working there 8 years in the space and 8 years in the guided missile division, being involved in dynamics and control of satellites, missile systems and airbag gas generator production. In 1982, Prof. Pfeiffer went back to University, as full Professor of Mechanics at the Technical University, Munich: Dean and Vice-Dean in the years 1992-1996, member of the University Senate, member of the DFG Senate from 1996-2002 (German Research Foundation), GAMM President and Vice-President 2002-2007 (Society of Applied Mechanics and Mathematics), committee chairman Belgium Research Foundation, member Council of the German Army University in Munich, Rector of CISM, Udine, Italy (International Centre for Mechanical Sciences). Prof. Pfeiffer is a member of national and international scientific and technical societies, editor and associate editor of some international scientific journals. He was consultant to automotive and mechanical engineering industry. His main academic achievements are non-smooth multibody dynamics, especially with respect to large contact problems, and robotics together with walking machines. He received many awards, published more than 200 papers, has written seven books and several book contributions. In 20 years he gave lectures for more than 20000 students and candidates for exams and supervised more than 80 dissertations.

B. Balachandran

B. Balachandran

University of Maryland

Title: Lyapunov's Contributions and Some Applied Nonlinear Dynamics

Abstract: Aleksandr Mikhailovich Lyapunov's contributions have had a significant influence on studies of nonlinear dynamics of a range of systems within engineering and outside engineering. These contributions, which are related to the stability of motion, include the Lyapunov function, Lyapunov vectors, and Lyapunov exponents. In the spirit of these contributions, applied nonlinear dynamics in the context of ship crane-load oscillations, underwater vehicle systems, and growth and decay of nonlinear waves will be addressed in this talk.

Biography: Dr. Balachandran received his B. Tech (Naval Architecture) from the Indian Institute of Technology, Madras, India, M.S. (Aerospace Engineering) from Virginia Tech, Blacksburg, VA, USA and Ph.D. (Engineering Mechanics) from Virginia Tech. Currently, he is a Minta Martin Professor of Engineering at the University of Maryland, where he has been since 1993. His research interests include nonlinear phenomena, dynamics and vibrations, and control. The publications that he has authored/co-authored include a Wiley textbook entitled "Applied Nonlinear Dynamics: Analytical, Computational, and Experimental Methods" (1995, 2004), a Cambridge University Press textbook entitled "Vibrations" (2019), and a co-edited Springer book entitled "Delay Differential Equations: Recent Advances and New Directions" (2009). Recently, he completed his terms as the Editor of the ASME Journal of Computational and Nonlinear Dynamics and a Contributing Editor of the International Journal of Non-Linear Mechanics. He is a Fellow of ASME and AIAA and a senior member of IEEE.

Join NSF Program Director, Dr. Kathryn Jablokow, to learn how the Engineering Design and Systems Engineering (EDSE) program is forging new, forward-looking directions for design research focused on responding to key societal needs and expanding the impact of emerging technologies. Practical strategies for submitting successful EDSE proposals will also be offered, along with time for Q&A. Come prepared to challenge your thinking, as we reflect on lessons learned over the past 18 months and how design research might play a role in expanding our vision of the "new future normal".

To help facilitate discussion and to better tailor the contents of the webinar to registrants, please fill out this brief survey by Tuesday, August 17th 2021.

Eleni Chatzi

Eleni Chatzi

ETH Zürich

Title: On the fusion of data and models; the hybrid path to Diagnosis & Prognosis of Monitored Systems

Abstract: The monitoring of the condition of engineered systems operating under diverse dynamic loads involves the tasks of simulation (forward engineering), identification (inverse engineering) and maintenance/control actions. The efficient and successful implementation of these tasks is however non-trivial, due to the ever-changing nature of these systems, the variability in their interactive environments, and the polymorphic uncertainties involved. Structural Health Monitoring (SHM) attempts to tackle these challenges by exploiting information stemming from sensor networks.

SHM comprises a hierarchy across levels of increasing complexity aiming to i) detect damage, ii) localize and iii) quantify damage, and iv) finally offer a prognosis over the system's residual life. When considering higher levels in this hierarchy, including damage assessment and even performance prognosis, purely data-driven methods are found to be lacking. For higher-level SHM tasks, or for furnishing a virtualization of a monitored system, it is necessary to integrate the knowledge stemming from physics-based representations, relying on the underlying mechanics and dynamics principles. This talk discusses implementation of such a hybrid approach to SHM for tackling the aforementioned challenges with examples across diverse systems including civil structures and transport infrastructure, as well as wind turbine facilities.

Biography: Eleni Chatzi is currently an Associate Professor and Chair of Structural Mechanics and Monitoring at the Department of Civil, Environmental and Geomatic Engineering of ETH Zürich. She received her PhD (2010) from the Department of Civil Engineering and Engineering Mechanics at Columbia University. Her research interests include the fields of Structural Health Monitoring (SHM) and structural dynamics, nonlinear system identification, and data-driven decision support for engineered systems. She is an author of over 280 papers in peer-reviewed journals and conference proceedings, and further serves as an editor for international journals in the domains of Dynamics and SHM. She led the recently completed ERC Starting Grant WINDMIL on the topic of "Smart Monitoring, Inspection and Life-Cycle Assessment of Wind Turbines". Her work in the domain of self-aware infrastructure was recognized with the 2020 Walter L. Huber Research prize, awarded by the American Society of Civil Engineers (ASCE).

Hanna Cho

Hanna Cho

The Ohio State University

Title: Constructive Utilization of Nonlinear Dynamics in Micro-scale Systems

Abstract: During the last decades, we have witnessed that various micro systems revolutionized fundamental and applied science. Due to their small size and low damping, these devices often exhibit significant nonlinearity and thus the operational range of these impressive applications shrinks. Therefore, understanding the mechanisms leading to nonlinearity in such systems will not only eliminate obstacles to their further development but also significantly enhance their performance. Motivated by the need to advance current capabilities of various micro-systems, my research has been focused on the implementation of intentional nonlinearity in the design of micro resonators to exploit various nonlinear phenomena, not attainable in linear settings, such as broadband resonances, dynamic instabilities, nonlinear hysteresis, and passive targeted energy transfers. We developed a comprehensive analytical, numerical, and experimental methodology to consider structural nonlinearity as a main design factor enabling to tailor mechanical resonances and achieve targeted performance. Our more recent works focus on exploiting nonlinearity and multimodality simultaneously by internally coupling two or more modes through the mechanism of internal resonance. This talk will introduce various types of nonlinearity realized in micro-systems and discuss their unique behavioral features that can be exploited in the field of MEMS and AFM.

Biography: Dr. Hanna Cho is an Associate Professor in the Department of Mechanical and Aerospace Engineering at The Ohio State University. Dr. Cho earned BS and MS degrees in Mechanical Engineering from Yonsei University, South Korea in 2002 and 2004, and a PhD at the University of Illinois at Urbana-Champaign (UIUC) in 2012. Cho’s research laboratory, the Micro/Nano Multiphysical Dynamics Laboratory, focuses on studying nonlinear dynamics in micro/nanomechanical systems to utilize beneficial nonlinear characteristics in developing novel Micro-Electro-Mechanical Systems (MEMS) such as sensing, imaging and energy harvesting; and multi-physical dynamics arising in atomic force microscopy (AFM) to advance state-of-the-art AFM. She is a Young Faculty Award and Director’s Fellowship recipient from Defense Advanced Research Project Agency (DARPA), and received Lumley Research Award (2020).

Kathleen Fitzsimons

Assistant Professor, Penn State

Title: Using Information Encoded in Motion to Close the loop in pHRI

Abstract: Robotics and haptics have the potential to enhance human performance and learning as well as provide unique insight into neuromotor function through sensing and quantification of human motion. At the same time, human behavior can inform the development of control strategies for complex tasks and human-robot interactions.

In physical human-robot interaction, information is communicated via motion — configurations, velocities, forces, and torques. The methods used for evaluation of motion greatly influences our ability to recognize the effects of assistance and training from a statistical standpoint, but more importantly, the mathematical structure imposed by unique measures of motion quality has significant impact on the algorithmic tools that are available to manage the interactions between robots and humans. This talk will focus on how motion measures affect the performance of the closed loop controller and our ability to statistically characterize differences in motion due to deficit, assistance, and learning.

Biography: Katie Fitzsimons is an Assistant Professor of Mechanical Engineering at the Pennsylvania State University. Prof. Fitzsimons earn her B.S. in Mechanical Engineering from Michigan State University in 2013, M.S. in Mechanical Engineering from Northwestern University in 2017, and Ph.D. from Northwestern in 2020. Dr. Fitzsimons' research interests lie at the interaction between humans and autonomous systems at both the level of an individual human-robot pair and the broader exchange between the fields of human motion analysis and robotic control. She was awarded the National Science Foundation Graduate Research Fellowship in 2014 and was awarded the National Defense Science and Engineering Graduate Fellowship in 2016.

 

Kuan-Lun Hsu

Assistant Professor
National Taiwan University>

Title: An introductory talk about the design of cam mechanisms

Abstract: Cam mechanisms have been widely implemented in modern applications, such as automatic tool changer (ATC), internal combustion engines, and pick-and-place machines. To improve the performance of these industrial applications using the cam mechanism, it is necessary to invent novel cam mechanisms that can overcome inherit disadvantages of commonly used types. Many of newly invented cam mechanisms with modified followers will be presented. Firstly, a disk cam mechanism with a translating follower that has symmetrical double rollers is found to have a better transmission angle on both the rising and the falling motions of the follower. Secondly, a positive-drive cam mechanism with dual concave faces of the follower is found to have lower contact stress over the constant-breadth and the constant-diameter cam mechanisms. At last, on the basis of an existing cam mechanism with a common roller follower, an extraneous intermediate link that has three rollers is added between the cam and the common follower. The contact forces and contact stresses of such cam mechanisms are analyzed to illustrate the advantage of spreading force transmission and reducing contact stress of this uncommon follower. In addition, the modified arrangement of the follower can be adapted to the stationary cam mechanism. Since the profiles of the stationary cam can be correspondingly determined according to desired path of the follower, the stationary cam mechanism can guide a follower with three rollers to move smoothly and free of backlash along a straight-curved stationary cam profile. Synthesis methodologies of these cam mechanisms will be shared during the Early Career Faculty Invited Presentation. Besides, it will be demonstrated that how these cam mechanisms could be a very economic and effective choice for the applications against a heavy loading or at a high speed.

Biography: Kuan-Lun Hsu is currently an assistant professor of Mechanical Engineering in National Taiwan University, Taipei, Taiwan. He holds a dual-degree at the doctoral level in Engineering at National Tsing Hua University and Tennessee Technological University. His research interests include kinematics and dynamics of machinery, mechanism and machine design, and cam-follower system.

 

Monroe Kennedy III

Assistant Professor
Stanford

Title: Considerations for Human-Robot Collaboration

Abstract: The field of robotics has evolved over the past few decades. We've seen robots progress from the automation of repetitive tasks in manufacturing to the autonomy of mobilizing in unstructured environments to the cooperation of swarm robots that are centralized or decentralized. These abilities have required advances in robotic hardware, modeling, and artificial intelligence. The next frontier is robots collaborating in complex tasks with human teammates, in environments traditionally configured for humans. While solutions to this challenge must utilize all of the advances of robotics, the human element adds a unique aspect that must be addressed. Collaborating with a human teammate means that the robot must have a contextual understanding of the task as well as all participant's roles. We will discuss what constitutes an effective teammate and how we can capture this behavior in a robotic collaborator. Biography: Monroe Kennedy III is an assistant professor in Mechanical Engineering at Stanford University. He leads the Assistive Robotics and Manipulation laboratory (arm.stanford.edu), which will develop robotic assistants by focusing on combining modeling and control techniques together with machine learning tools. Together, these techniques will improve performance for tasks that are highly dynamic, require dexterity, have considerable complexity, and require human-robot collaboration. Prof. Kennedy received his Ph.D. in Mechanical Engineering and Applied Mechanics and Masters in Robotics at the University of Pennsylvania, advised by Dr. Vijay Kumar, with a focus in robotics in the GRASP Lab. He was the recipient of GEM and NSF graduate fellowships. During his graduate studies, his research focused on increasing the abilities and effectiveness of robotic mobile manipulators performing complex service tasks in unstructured environments with considerations for working alongside human collaborators.

 

Carlotta Mummolo

Assistant Professor
New Jersey Institute of Technology

Title: Measures of Motor Performance in Human and Robots

Abstract: The proposed talk will cover two main topics, reflecting my current and future research directions. Both topics pertain to the fundamental research question of quantifying aspects of motor performance in general mechanisms.

In the first part of the talk, I will discuss the theoretical and computational framework that is being developed for the characterization of the limits of dynamic balance in general biped systems. A systematic characterization of a threshold of balance in the state space of a given system is discussed. This threshold gives a prediction on the balancing capabilities of a given biped model, in terms of quantifiable ranges of feasible center of mass position and velocity. The characteristic shape of this balance threshold, called Boundary of Balance, can guide the design of legged mechanisms based on predefined balance requirements. This research is under experimental validation and will be translated into a technology for the quantitative assessment and training of balance performance in home-care settings.

In the second part of the talk, a model of motor task difficulty will be discussed, inspired by measures of complexity that are derived from information theory, such as Shannon’s entropy. The concept of difficulty is associated with the ability of the end-effector of a moving agent (robot or human) to accomplish a trajectory during a certain motor task. This ability depends on the fit between external (environment) and internal (agent) constraints, also known as affordance. A stochastic model of difficulty for a generalized reaching motor task is proposed as an affordance-related measure of perceived difficulty for an agent in a given task and environment. This research will prompt new perspectives in the study of movement affordance arising in the mutual interaction of humans, robots, and their environments.

The discussed research aims at providing novel benchmarks of motor behavior, which are essential for evaluating motor performance in robots, as well as in the robot-assisted workforce and in patients affected by impaired mobility.

In the long term, both topics will help steer the research paradigm on human and robot motion and control towards the new perspective of morphological intelligence, in which the complex morphology of mechanisms (e.g., large number of degrees-of-freedom, big dimension of actuation space, etc.) is not seen as an obstacle, but a source of embodied intelligence that can reduce the centralized computational demand at the higher level (e.g., brain or CPU).

Biography: Carlotta Mummolo is an Assistant Professor in the Department of Biomedical Engineering at the New Jersey Institute of Technology. Since September 2018, she is the director of the Coppélia Research Lab, where a diverse team of students and researchers studies principles of robot manipulation, locomotion, and balance stability, with applications in the field of motor rehabilitation. Dr. Mummolo received her bachelor and master degrees in Mechanical Engineering from Polytechnic of Bari (Italy) in 2009 and 2011, respectively, and a second master degree in Mechanical Engineering from New York University (NYU) in 2011. In January 2016, she received two doctoral degrees through a joint Ph.D. program in Mechanical Engineering between Polytechnic of Bari and NYU. She is member of ASME, IEEE Robotics and Automation Society, the International Society of Posture and Gait Research, and the NY Academy of Science. Her work is currently funded by NJIT Newark College of Engineering and by the European Union H2020 program.

 

Jungwon Seo

Assistant Professor
The Hong Kong University of Science and Technology

Title: Design, Planning, and Control for Versatile Robotic Manipulation

Abstract: Robotic manipulation seeks to advance the way we handle objects of interest and interact with our environment using autonomous robotic systems. There are a wide range of applications such as transporting goods in warehouses, assembling parts in factories, and handling everyday objects to serve people directly, in which robots with advanced manipulation capabilities can be useful. In typical object manipulation scenarios, robots must be able to get a good hold on objects, transfer objects between secure grasps, and interact deliberately with the environment. Such tasks are still very difficult for robots today, whose versatility and dexterity are far below human levels. Achieving robotic dexterity and versatility in manipulation is thus one of the grand challenges in robotics. In this talk, I will introduce the research activities in my group on various robotic manipulation problems. Design, planning, and control techniques that will enable robots to skillfully manipulate objects and interact with the environment will be presented.

Biography: Jungwon Seo is an Assistant Professor of Mechanical and Aerospace / Electronic and Computer Engineering at The Hong Kong University of Science and Technology (HKUST), Clear Water Bay, Hong Kong. He is working towards advanced design, planning, and control for versatile robotic manipulation. He received a B.S. degree in Mechanical Engineering from Seoul National University, Seoul, Rep. of Korea. He earned his PhD from the General Robotics, Automation, Sensing and Perception (GRASP) Laboratory at the University of Pennsylvania, PA, USA. His honors include IEEE ICRA 2019 Best Paper Award in Robot Manipulation and IEEE ICRA 2014 Best Paper Award in Automation.

 

Yu She

Adjunct Assistant Professor
Purdue University

Title: Leveraging Embedded Vision Sensors to Improve Robot's Performance

Abstract: Unlike conventional industrial robots that are kept separated from humans to ensure safety, the next generation robots physically interact with humans in a shared workspace. Soft robots are made of soft materials. They are inherently safe and ideal to be deployed in a human shared environment. However, their deformation is very complex which leads to great challenges for precise perception. I address this problem with embedded vision sensors thanks to their rich visual information. The high-resolution image data is capable of dealing with the complex deformation generated by the soft robots. In addition to the robot itself, I care about the robotic manipulation skills. Soft objects are exceedingly common in our daily life such as cables, clothes, towels, and fruits. But robotic manipulation of soft objects is very challenging because soft objects are deformable. They have infinite degrees of freedom, and their modeling and control are both very difficult. I address this problem with vision-based tactile sensors, which are able to capture the complex states (locally) of the soft objects. In this talk, I will present some of my recent works in these areas. First, I will discuss the development of an exoskeleton-covered soft robotic gripper that employs embedded vision sensors providing high-resolution proprioception and tactile sensing simultaneously. Second, I will present a vision-based tactile sensor that achieves high-resolution 3D reconstruction and is favorable for robotic manipulation. Finally, I will discuss the application of the vision-based tactile sensor for a robotic cable manipulation task.

Biography: Yu She will be joining Purdue University School of Industry Engineering as an assistant professor in 2021 Fall. He is currently an adjunct assistant professor at Purdue University and a postdoctoral researcher at MIT Computer Science & Artificial Intelligence Laboratory (CSAIL). He received his PhD in Mechanical Engineering at Ohio State University. He studies theoretical modeling, algorithm implementation, and prototype manufacturing for soft robots, human-safe collaborative robots, and tactile-reactive robotic hands. He received the presidential fellowship at the Ohio State University. He was a recipient of the best paper finalist at the 2020 Robotics: Science and Systems (RSS), the best paper award at the 2018 ASME Dynamic Systems & Control Conference (DSCC), and the best paper finalist at the 2013 IEEE International Conference on Robotics and Biomimetics (ROBIO).

 

Cynthia Sung

Assistant Professor
University of Pennsylvania

Title: Dynamical Robots via Origami-Inspired Design

Abstract: Origami-inspired engineering produces structures with high strength-to-weight ratios and simultaneously lower manufacturing complexity. This reliable, customizable, cheap fabrication and component assembly technology is ideal for robotics applications in remote, rapid deployment scenarios that require platforms to be quickly produced, reconfigured, and deployed. Unfortunately, most examples of folded robots are appropriate only for small-scale, low-load applications. In this talk, I will discuss efforts in my group to expand origami-inspired engineering to robots with the ability to withstand and exert large loads and to execute dynamic behaviors. I will show how the computational models of an origami design allow us to explore and optimize its mechanical response, and how we can leverage these designs for better performance and simpler control.

Biography: Cynthia Sung is the Gabel Family Term Assistant Professor in the Department of Mechanical Engineering and Applied Mechanics (MEAM) and a member of the General Robotics, Automation, Sensing & Perception (GRASP) lab at the University of Pennsylvania. She received a Ph.D. in Electrical Engineering and Computer Science from MIT in 2016 and a B.S. in Mechanical Engineering from Rice University in 2011. Her research interests are computational methods for design automation of robotic systems, with a particular focus on origami-inspired and compliant robots. She is the recipient of a 2019 NSF CAREER award, 2020 Johnson & Johnson Women in STEM2D Scholars Award, and a 2017 Popular Mechanics Breakthrough Award.

 

Vishesh Vikas

Assistant Professor
University of Alabama

Title: Mobility and Morphing of Modular Soft Robots

Abstract: Soft materials are deemed attractive for applications where adaptability and safe interaction with the environment are imperative. Imagine a swarm of terrestrial robots that can explore an environment, and upon completion of this task, reconfigure into a spherical ball and roll out. Realizing such versatile and robust systems poses design and mobility challenges. Morphological and topology design of such soft robot modules is based in age-old geometry concepts of platonic solids. While the control challenges are addressed by adopting an environment-centric perspective where graph theory is used to construct a probabilistic model of the environment. This generic, adaptable, robust and learning-oriented framework allows us to represent complex locomotion tasks as integer linear programming optimization problems which can be easily solved using commercial, off-the-shelf solvers.

Biography: Vishesh Vikas is an assistant professor in the Department of Mechanical Engineering, University of Alabama, Tuscaloosa (UA) and the director of the Agile Robotics Lab at UA (www.arl.ua.edu). His research interests are in the field of soft robotics, bioinspired robotics and tensegrity mechanisms. He received his MS (2008) and PhD (2011) in Mechanical Engineering from the Center of Intelligent Machines and Robotics (CIMAR), University of Florida, Gainesville. Thereafter, he was a postdoctoral researcher at the Neuromechanics and Biomimetics Devices, Tufts University (2012-2016). He has served as the Chair of Student Mechanisms and Robotics Design Competition at the ASME IDETC (2017-2019). Currently, he serves on the Electronic Editorial Board for the ASME Journal of Mechanisms and Robotics (JMR).

 

Yujiang (Mike) Xiang

Assistant Professor
Oklahoma State University

Title: Optimal Control of Multiple Powered Exoskeletons for Symmetric Human Lifting

Abstract: In this study, the optimal control of multiple powered exoskeletons for symmetric lifting motion is presented. The two-dimensional human model has 10 degrees of freedom. Four powered exoskeletons at knee, hip, spine, and elbow joints are used to aid the lifting motion. Physics-based motor dynamics are modeled with human mechanical system which is built by recursive Lagrangian dynamics. The gradient-based optimization is used to find the optimal lifting motion and controls of powered exoskeletons at multiple joints. In the optimization formulation, the design variables are the exoskeleton motor current profiles and human joint angle profiles. The inverse dynamics are used to calculate human and exoskeleton joint torques. The cost function is to minimize the sum of human joint torque squares for the lifting motion. The human and exoskeletons’ optimal joint torque profiles are reported. The optimal solution is obtained in several seconds of CPU time. The coupling of multiple powered exoskeletons at different joints for lifting is studied.

Biography: Dr. Yujiang (Mike) Xiang is an assistant professor in Mechanical and Aerospace Engineering Department at Oklahoma State University (OSU). Before he joined OSU, he was an assistant professor in Mechanical Engineering Department at University of Alaska Fairbanks. His research focuses on dynamic motion planning, rehabilitation mechanism design, exoskeleton optimal control, and related biomechanical modeling and evaluation.