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City Sampling / / Company Ad Hoc Networks / Embedded Networked Sensor Systems / Intel / / Currency pence / / / Facility Massachusetts Institute of Technology / Computer Science Dept.† University of Southern California Los Angeles / / IndustryTerm underwater sensor networks / mobile sensor networks / wireless modems / motion planning algorithms / separated wireless sensor network / sensor networks / spatiotemporal monitoring applications / data collection using robotic sensor networks / stationary sensor network / motion planning algorithm / oil spills / robotic sensor networks / sparse sensor networks / wireless nodes / Wireless communications / wireless sensor networks / sub-networks / underwater sensor network / denser networks / wireless communications literature / i7 processor / underwater search / energy / / OperatingSystem Linux / Ubuntu / / Organization Electrical Engineering Dept.∗ and Computer Science Dept.† University of Southern California Los Angeles / National Science Foundation / Oregon State University / Massachusetts Institute of Technology / / Person E. Stump / V / Gaurav S. Sukhatme / / Position communication model / ” Int / amplify-and-forward / sampling-based motion planner / / Product Pentax K-x Digital Camera / / ProgrammingLanguage C++ / / ProvinceOrState Massachusetts / / Region Southern California / / Technology Sampling-based algorithms / RAM / RIG algorithm / sampling-based motion planning algorithm / extended algorithm / Linux / wireless communications / Mobile Computing / proposed algorithms / motion planning algorithm / simulation / motion planning algorithms / i7 processor / / SocialTag 
Squared Error Distortion Metrics for Motion Planning in Robotic Sensor Networks Geoffrey A. Hollinger Chiranjib Choudhuri∗ , Urbashi Mitra∗ and Gaurav S. Sukhatme†