People

Prof. Kira Barton (bartonkl@umich.edu) received her B.S. degree in Mechanical Engineering from the University of Colorado at Boulder in 2001. Barton continued her education in mechanical engineering at the University of Illinois at Urbana-Champaign and completed her M.S. and Ph.D. degrees in 2006 and 2010, respectively. She held a postdoctoral research position at the University of Illinois from Fall 2010 until Fall 2011, at which point she joined the Mechanical Engineering Department at the University of Michigan at Ann Arbor.

Her primary research focus is on precision coordination and motion control for emerging applications, with a specialization in iterative learning control. Barton’s work intersects controls and manufacturing and combines innovative manufacturing processes with enhanced engineering capabilities. The potential impact of this research ranges from building high-resolution DNA sensors for biological applications to the integration of advanced sensing and control for rehabilitation robotics.

Research Interests: Airborne wind energy, Iterative Learning Control, Optimization, Motion planning

Research Title: Economic Iterative Learning Control of Airborne Wind Energy Systems

Research Interests: Process Modeling and Control, Additive Manufacturing, Printed Electronics, E-jet Printing (EHD)

Research Title: Additive Nanomanufacturing for Customized Device Fabrication

Research Interests: Predictive maintenance, smart manufacturing, data science, and signal processing

Research Title: Adaptive modeling for predictive maintenance of manufacturing equipment

Research Interests: Multi-robot task planning, planning under uncertainty, machine learning, localization, mapping

Research Title: A Learning and Planning Framework for Robust Task Allocation for Heterogeneous Robot Teams

Research Interests: Data-driven robot skill learning; learning-based control for manipulators, heterogeneous robot teaming; smart manufacturing

Research Title: Learning Robot Skills from Data for Rapid Adaptation to Dynamic and Uncertain Industrial Environments

Research Interests: Wearable sensors for healthcare, human motion, human gait analysis, biomechanics, data science

Research Title: Investigating How Wearable Sensing Technologies can be Leveraged to Quantify Human Health

Research Interests: Multi-agent systems, agile supply chain, dynamic decision-making, smart manufacturing

Research Title: Distributed Decision-making in Disrupted Industrial Environments using a Multi-agent Framework

Research Interests: Controls, Smart Manufacturing, Digital Twins, Mechatronics

Research Title: Human Digital Twins for Human-Robot Collaboration in Manufacturing

Research Interests: Learning, Localization and Mapping

Research Interests: Wearable Sensors, Controls, Mechatronics, Human Motion, Biomechanics

Research Interests: E-Jet (EHD) Printing, Computational Fluid Dynamics (CFD) Modeling and Simulation, Additive Manufacturing, Control Theory

Research Interests: E-jet printing, modeling and simulation, additive manufacturing, system identification, and digital twins

Research Title: Data-based models of material properties, process parameters, and droplet characteristics using electrohydrodynamic jet printing

Research Interests: Industrial robotics, robotic manufacturing and machining, controls, sensing, mechatronic and embedded systems

Research Interests: Additive manufacturing, E-Jet Printing, Printed electronics, Manufacturing automation

Research Title: Manufacturing Autonomy: Process Model Development towards the Directed Evolution of Submicron Printed Lines Using Electrohydrodynamic Jet Printing

Research Interests: Battery state and control, multi-robot task planning, planning under uncertainty

Research Title: Controls for Shape-changing Solid State Batteries

Research Interests: Smart Manufacturing, Digital Twins, Manipulation, Motion Planning, Controls, Mechatronics

Project Description: Present a requirements framework to realize complete virtual commissioning. Virtual commissioning is the process of verification and/or validation of a manufacturing system’s process design and controls design, by using simulation technology and digital twins to confirm if the simulated or emulated performance metrics meet manufacturer requirements.

Research Interests: 3D Vision, Deep Learning for Robot Perception, Human-Robot Interaction, Mechatronics

Research Title: Neural Network-based Method for Human Intent Prediction in Dynamic Human-Robot Collaboration