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Geoff Hollinger's Nov. 2011 Visitor Talk

Speaker: Geoffrey A. Hollinger, Robotic Embedded Systems Laboratory, Viterbi School of Engineering, University of Southern California

Title: Robotic Decision Making for Sensing in the Natural World

Abstract: There is growing interest in the use of robots to gather information from natural environments. Examples include biological monitoring, mine sweeping, oil spill cleanup, and seismic event detection. The increasing capabilities of the robots themselves enable more sophisticated decision making techniques that optimize information gathered and adapt as new information is received. The question becomes: how do we develop path planning algorithms for information gathering tasks that are capable of dealing with the communication limitations, noisy sensing, and mobility restrictions present in natural environments?

This talk considers two problems related to path planning for Autonomous Underwater Vehicles (AUVs): (1) data gathering from an underwater sensor network equipped with acoustic communication and (2) autonomous inspection of the submerged portion of a ship hull. For the first problem, I present path planning methods that extend algorithms for variants of the Traveling Salesperson Problem (TSP) and show how these algorithms can be integrated with realistic acoustic communication models. For the second problem, I discuss techniques for constructing watertight 3D meshes from sonar-derived point clouds and introduce uncertainty modeling through non-parametric Bayesian regression. Uncertainty modeling provides novel cost functions for planning the path of the robot that allow for formal analysis through connections to submodular optimization and active learning. Such theoretical analysis provides insight into the underlying structure of active sensing problems. Finally, I present experiments that demonstrate the high performance of the proposed solutions versus the state of the art in robot path planning.

Speaker Bio: Geoffrey A. Hollinger is a Postdoctoral Research Associate in the Robotic Embedded Systems Laboratory and Viterbi School of Engineering at the University of Southern California. He is currently interested in adaptive sensing and distributed coordination for underwater robots operating with limited communication. He has also worked on multi-robot search at Carnegie Mellon University, personal robotics at Intel Research Pittsburgh, active estimation at the University of Pennsylvania's GRASP Laboratory, and miniature inspection robots for the Space Shuttle at NASA's Marshall Space Flight Center. He received his Ph.D. (2010) and M.S. (2007) in Robotics from Carnegie Mellon University and his B.S. in General Engineering along with his B.A. in Philosophy from Swarthmore College (2005).