Research Initiation Award: Cognitive Monitoring Systems using Intelligent Robots and Sensors in Dynamic Extreme Environments

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Research Initiation Awards provide support for junior and mid-career faculty at Historically Black Colleges and Universities who are building new research programs or redirecting and rebuilding existing research programs. It is expected that the award helps to further the faculty member's research capability and effectiveness, improves research and teaching at the home institution, and involves undergraduate students in research experiences. The award to Norfolk State University (NSU) has potential broader impacts in a number of areas. The goal of this project is to develop cognitive monitoring systems using intelligent sensors and robots to provide real-time sensing and wireless localization in metallic oil pipelines. The project is a collaborative effort between faculty at NSU and Old Dominion University and involves undergraduate students in the research.This project leverages the cooperation between intelligent underground sensors and in-pipe robots to enable automated cognitive monitoring of metallic pipelines in dynamic underground environments. Underground pipeline leakages caused by internal and external corrosions create significant economic loss and environmental contamination. Wireless in-pipe robots are used to provide precise internal inspections and underground sensors to detect leakages and relay wireless data for in-pipe robots. The specific research aims are to: design reliable through-metal and through-soil wireless communication systems using magnetic induction; intelligently control robots' motion and communication; develop robust wireless networks considering the dynamic change of extreme environments; and design experimental testbeds. The research makes theoretical and empirical contributions to wireless sensing and cognitive monitoring in extreme environments. Findings will improve the accuracy of leakage prediction and detection for underground pipelines, as well as contribute to a wider vision of automating dirty, dull, and dangerous tasks in harsh environments.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.