Due to circumstances beyond our control, today’s seminar has been cancelled.

Abstract

As the world is getting instrumented with numerous sensors, cameras, and robots, there is potential to transform industries as diverse as environmental monitoring, search and rescue, security and surveillance, localization and mapping, and structure inspection. Successful estimation techniques for gathering information in these scenarios have been designed and implemented. However, one of the great technical challenges today is to intelligently control the sensors, cameras, and robots in order to extract information actively and autonomously. In this talk, I will present a unified approach for active information acquisition, aimed at improving the accuracy and efficiency of tracking evolving phenomena of interest. I formulate a decision problem for maximizing relevant information measures and focus on the design of scalable control strategies for multiple sensing systems. First, I will present a greedy approach for information acquisition via applications in source seeking and mobile robot localization. Next, information acquisition with a longer planning horizon will be considered in the context of linear Gaussian models. I will develop an approximation algorithm with suboptimality guarantees to reduce the complexity in the planning horizon and the number of sensors and will present an application to active multi-robot localization and mapping. Finally, non-greedy information acquisition with general sensing models will be used for active object recognition. The techniques presented in this talk offer an effective and scalable approach for controlled information acquisition with multiple sensing systems.

Speaker Bio

George J. Pappas is the Joseph Moore Professor and Chair of the Department of Electrical and Systems Engineering at the University of Pennsylvania. He also holds a secondary appointment in the Departments of Computer and Information Sciences, and Mechanical Engineering and Applied Mechanics. He is member of theGRASP Lab and the PRECISE Center. He has previously served as the Deputy Dean for Research in the School of Engineering and Applied Science. His research focuses on control theory and in particular, hybrid systems, embedded systems, hierarchical and distributed control systems, with applications to unmanned aerial vehicles, distributed robotics, green buildings, and biomolecular networks. He is a Fellow of IEEE, and has received various awards such as the Antonio Ruberti Young Researcher Prize, the George S. Axelby Award, theO. Hugo Schuck Best Paper Award, and the National Science Foundation PECASE.