Woodruff School of Mechanical Engineering
Faculty Candidate Seminar
Data-Driven Design of Adaptive Robotic Manipulators and Medical Devices
Dr. Frank Hammond III
Harvard University Biorobotics and the Harvard Microrobotics Laboratories
Monday, June 23, 2014 at 11:00:00 AM
MRDC Building, Room 4211
The design of effective robotic manipulators and medical devices requires careful selection of mechanical system components, proper design of actuation topologies and morphological configurations, and understanding of the manipulation tasks and medical conditions they are intended to address. Due to the complexity of the intended tasks and the immense size of the design spaces, developing these devices is non-trivial and can easily lead to solutions that are expensive, exorbitantly complex, and lacking the intended functionality and versatility. My work demonstrates how use of well-formulated numerical models, simulation methods, optimization frameworks, and the analysis of empirical data can mitigate mechanical complexity and elucidate salient design features to help us arrive at more functional and flexible robotic manipulation devices for a variety of applications. I will discuss several examples of this design strategy, beginning with the use of heuristic, multi-objective fitness measures and evolutionary optimization algorithms to design adaptive, kinematically redundant robotic manipulators. This novel design approach produces manipulators that can resolve kinematic redundancy to achieve secondary goals such as energy efficiency and robustness in unstructured environments, improving the economy and flexibility of automated industrial tasks while preserving dexterity, precision, and design simplicity. Next, I will focus on the use of numerical grasp simulation and analysis techniques to optimize the design of underactuated robotic hands. In particular, I will discuss the derivation of non-anthropomorphic grasp synergies using an actuation topology reduction method, as well as the numerical exploration of the vast robotic hand design space to determine the viability of xenomorphic hand morphologies which, despite their unnatural appearance, may prove more adept at grasping certain classes of objects than human hands. I will then describe the data-driven design of a dexterous robotic micromanipulation system for microsurgery, and how analyzing empirical data gathered from tracking the motion of surgical micromanipulation instruments can lead to the specification of more reliable and comprehensive system performance requirements. These requirements are used to optimize the kinematic and mechanical design of the robotic micromanipulation system to exceed manual micromanipulation capabilities, such as dexterity, precision, and repeatability – enabling new, more effective surgical intervention techniques. Finally, I will present recent work on the development of soft sensors and printable strain gauges, and discuss future research topics and potential applications of this contextual modeling and design optimization strategy to human motion augmentation, adaptive robotic manipulation, and bioinspired mobile robots.
Frank L. Hammond III is currently a Ford Postdoctoral Research Fellow in the Harvard Biorobotics and the Harvard Microrobotics Laboratories. His primary research interests lie in using numerical modeling and optimization methods to inform the design of redundant robotic manipulators and bioinspired mobile robots, robotic surgery platforms, and innovative devices for human motion sensing and augmentation. He is actively conducting research on dexterous robotic micromanipulation for teleoperative microsurgery at the Wyss Institute for Biologically Inspired Engineering at Harvard University. He is also active in NSF-funded research on underactuated robotic grasping and is spearheading new research on soft wearable sensors and robotic actuators, and printable strain gauges for force measurement in the Harvard Microrobotics Laboratory. Frank received his B.S. degree in Electrical Engineering from Drexel University in 2002, his M.S. degrees in Electrical Engineering and Mechanical Engineering from the University of Pennsylvania in 2006, and his PhD in Mechanical Engineering from Carnegie Mellon University in 2010. As a postdoctoral research fellow at Harvard University, Frank won the Ford Postdoctoral Research Fellowship which has funded much of his work on dexterous robotic micromanipulation.
Refreshments will be served.