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

研究启动奖为历史悠久的黑人学院和大学的初级和职业生涯中期教师提供支持，这些教师正在建立新的研究计划或重新定向和重建现有的研究计划。预计该奖项有助于进一步提高教师的研究能力和有效性，改善所在机构的研究和教学，并让本科生参与研究经验。授予诺福克州立大学(NSU)的奖项可能在许多领域产生更广泛的影响。该项目的目标是开发使用智能传感器和机器人的认知监控系统，以提供金属输油管道的实时传感和无线定位。该项目是NSU和Old Dominion大学教职员工的合作成果，本科生参与了这项研究。该项目利用智能地下传感器和管道内机器人之间的合作，实现了对动态地下环境中金属管道的自动化认知监控。由内外腐蚀引起的地下管线泄漏造成了巨大的经济损失和环境污染。无线管道机器人用于为管道机器人提供精确的内部检测和地下传感器，以检测泄漏并传递无线数据。具体的研究目标是：利用磁感应设计可靠的穿透金属和穿透土壤的无线通信系统；智能控制机器人的运动和通信；考虑极端环境的动态变化开发健壮的无线网络；以及设计实验试验台。本研究为极端环境下的无线传感和认知监测做出了理论和经验上的贡献。这一发现将提高地下管道泄漏预测和检测的准确性，并有助于在恶劣环境中自动执行肮脏、枯燥和危险的任务的更广泛的愿景。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.