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Inspection of ship hulls and marine structures using autonomous underwater vehicles has emerged as a unique and challenging application of robotics. The problem poses rich questions in physical design and operation, perception and navigation, and planning, driven by difficulties arising from the acoustic environment, poor water quality and the highly complex structures to be inspected. In this paper, we develop and apply algorithms for the central navigation and planning problems on ship hulls. These divide into two classes, suitable for the open, forward parts of a typical monohull, and for the complex areas around the shafting, propellers and rudders. On the open hull, we have integrated acoustic and visual mapping processes to achieve closed-loop control relative to features such as weld-lines and biofouling. In the complex area, we implemented new large-scale planning routines so as to achieve full imaging coverage of all the structures, at a high resolution. We demonstrate our approaches in recent operations on naval ships.

Endoplasmic reticulum (ER) stress is associated with liver injury and fibrosis, and yet the hepatic factors that regulate ER stress-mediated inflammasome activation remain unknown. Here, we report that farnesoid X receptor (FXR) activation inhibits ER stress-induced NACHT, LRR, and PYD domains-containing protein 3 (NLRP3) inflammasome in hepatocytes. In patients with hepatitis B virus (HBV)-associated hepatic failure or non-alcoholic fatty liver disease, and in mice with liver injury, FXR levels in the liver inversely correlated with the extent of NLRP3 inflammasome activation. Fxr deficiency in mice augmented the ability of ER stress to induce NLRP3 and thioredoxin-interacting protein (TXNIP), whereas FXR ligand activation prevented it, ameliorating liver injury. FXR attenuates CCAAT-enhancer-binding protein homologous protein (CHOP)-dependent NLRP3 overexpression by inhibiting ER stress-mediated protein kinase RNA-like endoplasmic reticulum kinase (PERK) activation. Our findings implicate miR-186 and its target, non-catalytic region of tyrosine kinase adaptor protein 1 (NCK1), in mediating the inhibition of ER stress by FXR. This study provides the insights on how FXR regulation of ER stress ameliorates hepatocyte death and liver injury and on the molecular basis of NLRP3 inflammasome activation.

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Abstract-This paper reports on a real-time monocular visual simultaneous localization and mapping (SLAM) algorithm and results for its application in the area of autonomous underwater ship hull inspection. The proposed algorithm overcomes some of the specific challenges associated with underwater visual SLAM, namely limited field of view imagery and feature-poor regions. It does so by exploiting our SLAM navigation prior within the image registration pipeline and by being selective about which imagery is considered informative in terms of our visual SLAM map. A novel online bag-of-words measure for intraand inter-image saliency are introduced, and are shown to be useful for image key-frame selection, information-gain based link hypothesis, and novelty detection. Results from three real-world hull inspection experiments evaluate the overall approachincluding one survey comprising a 3.4 hour / 2.7 km long trajectory.

The high diversity of urban environments, at both the inter and intra levels, poses challenges for robotics research. Such challenges include discrepancies in urban features between cities and the deterioration of sensor measurements within a city. With such diversity in consideration, this paper aims to provide Light Detection and Ranging (LiDAR) and image data acquired in complex urban environments. In contrast to existing datasets, the presented dataset encapsulates various complex urban features and addresses the major issues of complex urban areas, such as unreliable and sporadic Global Positioning System (GPS) data, multi-lane roads, complex building structures, and the abundance of highly dynamic objects. This paper provides two types of LiDAR sensor data (2D and 3D) as well as navigation sensor data with commercial-level accuracy and high-level accuracy. In addition, two levels of sensor data are provided for the purpose of assisting in the complete validation of algorithms using consumer-grade sensors. A forward-facing stereo camera was utilized to capture visual images of the environment and the position information of the vehicle that was estimated through simultaneous localization mapping (SLAM) are offered as a baseline. This paper presents 3D map data generated by the SLAM algorithm in the LASer (LAS) format for a wide array of research purposes, and a file player and a data viewer have been made available via the Github webpage to allow researchers to conveniently utilize the data in a Robot Operating System (ROS) environment. The provided file player is capable of sequentially publishing large quantities of data, similar to the rosbag player. The dataset in its entirety can be found at http://irap.kaist.ac.kr/dataset.

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This paper reports on an integrated navigation algorithm for the visual simultaneous localization and mapping (SLAM) robotic area coverage problem. In the robotic area coverage problem, the goal is to explore and map a given target area within a reasonable amount of time. This goal necessitates the use of minimally redundant overlap trajectories for coverage efficiency; however, visual SLAM's navigation estimate will inevitably drift over time in the absence of loop-closures. Therefore, efficient area coverage and good SLAM navigation performance represent competing objectives. To solve this decision-making problem, we introduce perception-driven navigation, an integrated navigation algorithm that automatically balances between exploration and revisitation using a reward framework. This framework accounts for SLAM localization uncertainty, area coverage performance, and the identification of good candidate regions in the environment for visual perception. Results are shown for both a hybrid simulation and real-world demonstration of a visual SLAM system for autonomous underwater ship hull inspection.