Subterranean openings, including mines, present a unique and challenging environment for robots and autonomous exploration systems. Autonomous robots that are created today will be deployed in harsh and unexplored landscapes that humanity is increasingly encountering in its scientific and technological endeavors. Terrestrial and extraterrestrial environments pose significant challenges for both humans and robots: they are inhospitable and inaccessible to humans due to a lack of space or oxygen, poor or no illumination, unpredictable terrain, a GPS-denied environment, and a lack of satellite imagery or mapping information of any type. Underground mines provide a good physical simulation for these types of environments, and thus, can be useful for testing and developing highly sought-after autonomous navigation frameworks for autonomous agents. This review presents a collective study of robotic systems, both of individual and hybrid types, intended for deployment in such environments. The prevalent configurations, practices for their construction and the hardware equipment of existing multi-agent hybrid robotic systems will be discussed. It aims to provide a supplementary tool for defining the state of the art of coupled Unmanned Ground Vehicle (UGV)–Unmanned Aerial Vehicle (UAV) systems implemented for underground exploration and navigation purposes, as well as to provide some suggestions for multi-agent robotic system solutions, and ultimately, to support the development of a semi-autonomous hybrid UGV–UAV system to assist with mine emergency responses.
This paper explores the use of acoustic-based structural health monitoring (SHM) in lunar habitats to detect damage and failure in pipelines used for resource transportation. Acoustic-based SHM on Earth is a well-studied field of research. Various studies validate the effectiveness of acoustic-based SHM to detect, locate, and characterize damage in pipelines. Relevant literature shows that little to no research has been conducted on SHM regarding simulated lunar pipelines. In this paper, acoustic emission (AE) waveforms were collected and analyzed for aluminum pipe sections that were damaged from three separately simulated lunar conditions. Experiments simulating lunar regolith abrasion, internal galvanic corrosion, and irradiation were conducted on aluminum pipes. Pipes on the lunar surface will be constantly exposed to radiation, abrasion, and corrosion. As such, it is important to detect, localize, and predict damage resulting from these lunar hazards. The waveform data were clustered based on hit-driven properties. These clusters showed distinct differences between the datasets, which allowed for comparison and characterization of the data. It was found that variations in cluster shape and placement in peak, centroid, and average frequency could reliably distinguish between corrosive and abrasive processes. Understanding the differences in the data that contribute to distinctions between event types, and those that do not, will enable AE monitoring systems to better identify, characterize, and predict lunar pipeline failure.
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