Hybrid Visual SLAM for Underwater Vehicle Manipulator Systems

This paper presents a novel visual scene mapping method for underwater vehicle manipulator systems (UVMSs), with specific emphasis on robust mapping in natural seafloor environments. Prior methods for underwater scene mapping typically process the data offline, while existing underwater SLAM methods that run in real-time are generally focused on localization and not mapping. Our method uses GPU accelerated SIFT features in a graph optimization framework to build a feature map. The map scale is constrained by features from a vehicle mounted stereo camera, and we exploit the dynamic positioning capability of the manipulator system by fusing features from a wrist mounted fisheye camera into the map to extend it beyond the limited viewpoint of the vehicle mounted cameras. Our hybrid SLAM method is evaluated on challenging image sequences collected with a UVMS in natural deep seafloor environments of the Costa Rican continental shelf margin, and we also evaluate the stereo only mode on a shallow reef survey dataset. Results on these datasets demonstrate the high accuracy of our system and suitability for operating in diverse and natural seafloor environments.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Towards Bathymetry-Optimized Doppler Re-Navigation for AUVs

This paper describes a terrain-aided re-navigation algorithm for autonomous underwater vehicles (AUVs) built around optimizing bottom-lock Doppler velocity log (DVL) tracklines relative to a ship derived bathymetric map. The goal of this work is to improve the precision of AUV DVLbased navigation for near-seafloor science by removing the lowfrequency “drift” associated with a dead-reckoned (DR) Doppler navigation methodology. To do this, we use the discrepancy between vehicle-derived vs. ship-derived acoustic bathymetry as a corrective error measure in a standard nonlinear optimization framework. The advantage of this re-navigation methodology is that it exploits existing ship-derived bathymetric maps to improve vehicle navigation without requiring additional infrastructure. We demonstrate our technique for a recent AUV survey of largescale gas blowout features located along the U.S. Atlantic margin.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86050/1/reustice-30.pd

Creation and deployment of the NEREUS autonomous underwater chemical analyzer and Kemonaut, an odyssey class submarine

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2003.Includes bibliographical references (p. 175-181).NEREUS is a compact self-contained low-power submersible membrane-inlet mass spectrometer, designed to measure dissolved volatile gasses in the water column. It is capable of intelligent data collection, analysis and state-based mission control while operating as a stand-alone instrument or onboard the Kemonaut autonomous underwater vehicle (AUV). Kemonaut is an Odyssey class AUV with increased payload carrying capacity and dynamic stability, and is intended for freshwater and coastal marine applications to depths of 300 meters. The NEREUS-Kemonaut system characteristics allow for greatly improved dissolved gas data collection rates, accuracy and mapping resolution over presently available technologies. Applications particularly well suited for the NEREUS-Kemonaut system include identification and mapping of pollution sources such as chemical spills, investigation of enigmatic freshwater and marine ecosystems, assessment of subsurface natural resources and estimation of marine-related greenhouse gas cycling.by Richard Camilli.Ph.D

The development of components for an in-situ mass spectrometer

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2000.Includes bibliographical references (p. 63-65).by Richard Camilli.S.M

Toward autonomous exploration in confined underwater environments

Author Posting. © The Author(s), 2015. This is the author's version of the work. It is posted here by permission of John Wiley & Sons for personal use, not for redistribution. The definitive version was published in Journal of Field Robotics 33 (2016): 994-1012, doi:10.1002/rob.21640.In this field note we detail the operations and discuss the results of an experiment conducted in the unstructured environment of an underwater cave complex, using an autonomous underwater vehicle (AUV). For this experiment the AUV was equipped with two acoustic sonar to simultaneously map the caves’ horizontal and vertical surfaces. Although the caves’ spatial complexity required AUV guidance by a diver, this field deployment successfully demonstrates a scan matching algorithm in a simultaneous localization and mapping (SLAM) framework that significantly reduces and bounds the localization error for fully autonomous navigation. These methods are generalizable for AUV exploration in confined underwater environments where surfacing or pre-deployment of localization equipment are not feasible and may provide a useful step toward AUV utilization as a response tool in confined underwater disaster areas.This research work was partially sponsored by the EU FP7-Projects: Tecniospring- Marie Curie (TECSPR13-1-0052), MORPH (FP7-ICT-2011-7-288704), Eurofleets2 (FP7-INF-2012-312762), and the National Science Foundation (OCE-0955674)

Coupled radon, methane and nitrate sensors for large-scale assessment of groundwater discharge and non-point source pollution to coastal waters

Author Posting. © The Author(s), 2009. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Journal of Environmental Radioactivity 101 (2010): 553-563, doi:10.1016/j.jenvrad.2009.12.004.We constructed a survey system of radon/methane/nitrate/salinity to find sites of submarine groundwater discharge (SGD) and groundwater nitrate input. We deployed the system in Waquoit Bay and Boston Harbor, MA where we derived SGD rates using a mass balance of radon with methane serving as a fine resolution qualitative indicator of groundwater. In Waquoit Bay we identified several locations of enhanced groundwater discharge, out of which two (Childs and Quashnet Rivers) were studied in more detail. The Childs River was characterized by high nitrate input via groundwater discharge, while the Quashnet River SGD was notable but not a significant source of nitrate. Our radon survey of Boston Harbor revealed several sites with significant SGD, out of these Inner Harbor and parts of Dorchester Bay and Quincy Bay had groundwater fluxes accompanied by significant water column nitrogen concentrations. The survey system has proven effective in revealing areas of SGD and non-point source pollution.R. Camilli acknowledges the National Ocean Partnership Program (NOPP) for supporting the development of the TETHYS mass spectrometer through research grant #OCE-0537173. H. Dulaiova, M. A. Charette and R. Camilli acknowledge funding support from the WHOI Coastal Institute and MIT Sea Grant College Program under NOAA grant number NA06OAR4170019, project number 5710002173. H. Dulaiova was funded by the WHOI Academic Program’s postdoctoral scholarship

Towards automated sample collection and return in extreme underwater environments

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Billings, G., Walter, M., Pizarro, O., Johnson-Roberson, M., & Camilli, R. Towards automated sample collection and return in extreme underwater environments. Journal of Field Robotics, 2(1), (2022): 1351–1385, https://doi.org/10.55417/fr.2022045.In this report, we present the system design, operational strategy, and results of coordinated multivehicle field demonstrations of autonomous marine robotic technologies in search-for-life missions within the Pacific shelf margin of Costa Rica and the Santorini-Kolumbo caldera complex, which serve as analogs to environments that may exist in oceans beyond Earth. This report focuses on the automation of remotely operated vehicle (ROV) manipulator operations for targeted biological sample-collection-and-return from the seafloor. In the context of future extraterrestrial exploration missions to ocean worlds, an ROV is an analog to a planetary lander, which must be capable of high-level autonomy. Our field trials involve two underwater vehicles, the SuBastian ROV and the Nereid Under Ice (NUI) hybrid ROV for mixed initiative (i.e., teleoperated or autonomous) missions, both equipped seven-degrees-of-freedom hydraulic manipulators. We describe an adaptable, hardware-independent computer vision architecture that enables high-level automated manipulation. The vision system provides a three-dimensional understanding of the workspace to inform manipulator motion planning in complex unstructured environments. We demonstrate the effectiveness of the vision system and control framework through field trials in increasingly challenging environments, including the automated collection and return of biological samples from within the active undersea volcano Kolumbo. Based on our experiences in the field, we discuss the performance of our system and identify promising directions for future research.This work was funded under a NASA PSTAR grant, number NNX16AL08G, and by the National Science Foundation under grants IIS-1830660 and IIS-1830500. The authors would like to thank the Costa Rican Ministry of Environment and Energy and National System of Conservation Areas for permitting research operations at the Costa Rican shelf margin, and the Schmidt Ocean Institute (including the captain and crew of the R/V Falkor and ROV SuBastian) for their generous support and making the FK181210 expedition safe and highly successful. Additionally, the authors would like to thank the Greek Ministry of Foreign Affairs for permitting the 2019 Kolumbo Expedition to the Kolumbo and Santorini calderas, as well as Prof. Evi Nomikou and Dr. Aggelos Mallios for their expert guidance and tireless contributions to the expedition

Contacts between the endoplasmic reticulum and other membranes in neurons

The cytoplasm of eukaryotic cells is compartmentalized by intracellular membranes that define subcellular organelles. One of these organelles, the endoplasmic reticulum, forms a continuous network of tubules and cisternae that extends throughout all cell compartments, including neuronal dendrites and axons. This network communicates with most other organelles by vesicular transport, and also by contacts that do not lead to fusion but allow cross-talk between adjacent bilayers. Though these membrane contacts have previously been observed in neurons, their distribution and abundance has not been systematically analyzed. Here, we have carried out such analysis. Our studies reveal new aspects of the internal structure of neurons and provide a critical complement to information about interorganelle communication emerging from functional and biochemical studies

Using a Ladder of Seeps with computer decision processes to explore for and evaluate cold seeps on the Costa Rica active margin

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Vrolijk, P., Summa, L., Ayton, B., Nomikou, P., Huepers, A., Kinnaman, F., Sylva, S., Valentine, D., & Camilli, R. Using a Ladder of Seeps with computer decision processes to explore for and evaluate cold seeps on the Costa Rica active margin. Frontiers in Earth Science, 9, (2021): 601019, https://doi.org/10.3389/feart.2021.601019.Natural seeps occur at the seafloor as loci of fluid flow where the flux of chemical compounds into the ocean supports unique biologic communities and provides access to proxy samples of deep subsurface processes. Cold seeps accomplish this with minimal heat flux. While individual expertize is applied to locate seeps, such knowledge is nowhere consolidated in the literature, nor are there explicit approaches for identifying specific seep types to address discrete scientific questions. Moreover, autonomous exploration for seeps lacks any clear framework for efficient seep identification and classification. To address these shortcomings, we developed a Ladder of Seeps applied within new decision-assistance algorithms (Spock) to assist in seep exploration on the Costa Rica margin during the R/V Falkor 181210 cruise in December, 2018. This Ladder of Seeps [derived from analogous astrobiology criteria proposed by Neveu et al. (2018)] was used to help guide human and computer decision processes for ROV mission planning. The Ladder of Seeps provides a methodical query structure to identify what information is required to confirm a seep either: 1) supports seafloor life under extreme conditions, 2) supports that community with active seepage (possible fluid sample), or 3) taps fluids that reflect deep, subsurface geologic processes, but the top rung may be modified to address other scientific questions. Moreover, this framework allows us to identify higher likelihood seep targets based on existing incomplete or easily acquired data, including MBES (Multi-beam echo sounder) water column data. The Ladder of Seeps framework is based on information about the instruments used to collect seep information (e.g., are seeps detectable by the instrument with little chance of false positives?) and contextual criteria about the environment in which the data are collected (e.g., temporal variability of seep flux). Finally, the assembled data are considered in light of a Last-Resort interpretation, which is only satisfied once all other plausible data interpretations are excluded by observation. When coupled with decision-making algorithms that incorporate expert opinion with data acquired during the Costa Rica experiment, the Ladder of Seeps proved useful for identifying seeps with deep-sourced fluids, as evidenced by results of geochemistry analyses performed following the expedition.Support for this research was provided through NASA PSTAR Grant #NNX16AL08G and National Science Foundation Navigating the New Arctic grant #1839063. Use of the R/V Falkor and ROV SuBastian were provided through a grant from the Schmidt Ocean Institute. The AUG Nemesis and the Aurora in-situ mass spectrometer was provided through in-kind support from Teledyne Webb Research and Navistry Corp, respectively

Self-assembly of ordered graphene nanodot arrays (vol 8, 47, 2017)

Change History: A correction to this article has been published and is linked from the HTML version of this article