Three faculty members in the Holcombe Department of Electrical and Computer Engineering have been awarded substantial research grants from the National Science Foundation.
Lin Zhu, Warren Owen Assistant Professor, has been awarded a $300,000 grant from NSF's Division of Electrical, Communications and Cyber Systems. The objective of Zhu's research is to control optical gradient forces in lightwave circuits through waveguide dispersion, to enhance optical gradient forces by using plasmonic effects, and to create novel resonant optomechanical devices. Optical gradient forces can be generated between integrated optical components by light and be used to control both optical and mechanical behavior of these components. The resulting integrated optomechanical devices provide a fascinating system to study the coupling between optics and mechanics.
Zhu and his research group will investigate new methods, such as waveguide dispersion and plasmonic effects, to manipulate and enhance optical gradient forces and explore new applications of these methods. Zhu hopes his work will lead to the creation of novel devices for information processing and fundamental physics. The outcome of his research will have significant impacts across many disciplines, such as light-controlled biomechanical manipulation and detection, photonic information processing, and strong light-matter interactions.
Stan Birchfield, Associate Professor, and Ian Walker, CoES IDEaS Professor, have been awarded a $400,000 grant from NSF's Division of Information and Intelligent Systems to conduct research that explores the concept of interactive perception or manipulated-guided sensing. In this project, successive manipulations of objects in an environment are used to increase vision-based understanding of that environment, and vice versa. Traditional robotics research has adopted a "sense-plan-act" paradigm in which it is assumed that the sensors are capable of providing enough information in order to decide the next course of action. Humans and animals, however, frequently adopt a different approach, such as shuffling through a pile of unknown objects in order to identify an item of interest hidden beneath the pile. In particular, the project involves developing appropriate low-order models of highly non-rigid structures such as fabrics and textiles; constructing algorithms to perform real-time vision-based sensing of such objects in cluttered, unstructured environments; and building prototype robotic hardware for testing the resulting models and algorithms. The research forms an integral part of next-generation household service robots performing everyday tasks such as sorting and folding laundry.
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