1
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Verma V, Maimone MW, Gaines DM, Francis R, Estlin TA, Kuhn SR, Rabideau GR, Chien SA, McHenry MM, Graser EJ, Rankin AL, Thiel ER. Autonomous robotics is driving Perseverance rover's progress on Mars. Sci Robot 2023; 8:eadi3099. [PMID: 37494463 DOI: 10.1126/scirobotics.adi3099] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 06/29/2023] [Indexed: 07/28/2023]
Abstract
NASA's Perseverance rover uses robotic autonomy to achieve its mission goals on Mars. Its self-driving autonomous navigation system (AutoNav) has been used to evaluate 88% of the 17.7-kilometer distance traveled during its first Mars year of operation. Previously, the maximum total autonomous distance evaluated was 2.4 kilometers by the Opportunity rover during its 14-year lifetime. AutoNav has set multiple planetary rover records, including the greatest distance driven without human review (699.9 meters) and the greatest single-day drive distance (347.7 meters). The Autonomous Exploration for Gathering Increased Science (AEGIS) system analyzes wide-angle imagery onboard to autonomously select targets for observations by the SuperCam instrument, a multimode sensor suite capable of millimeter-scale geochemical and mineralogical analysis. AEGIS enables observations of scientifically interesting targets during or immediately after long drives without the need for ground communication. OnBoard Planner (OBP) is a scheduling capability planned for operational use in September 2023 that has the potential to reduce energy usage by up to 20% and complete drive and arm-contact science campaigns in 25% fewer days on Mars. This paper presents an overview of the AutoNav, AEGIS, and OBP capabilities used on Perseverance.
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Affiliation(s)
- Vandi Verma
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
| | - Mark W Maimone
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
| | - Daniel M Gaines
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
| | - Raymond Francis
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
| | - Tara A Estlin
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
| | - Stephen R Kuhn
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
| | - Gregg R Rabideau
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
| | - Steve A Chien
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
| | - Michael M McHenry
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
| | - Evan J Graser
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
| | - Arturo L Rankin
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
| | - Ellen R Thiel
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
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2
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Theiling BP, Chou L, Da Poian V, Battler M, Raimalwala K, Arevalo R, Neveu M, Ni Z, Graham H, Elsila J, Thompson B. Science Autonomy for Ocean Worlds Astrobiology: A Perspective. ASTROBIOLOGY 2022; 22:901-913. [PMID: 35507950 DOI: 10.1089/ast.2021.0062] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Astrobiology missions to ocean worlds in our solar system must overcome both scientific and technological challenges due to extreme temperature and radiation conditions, long communication times, and limited bandwidth. While such tools could not replace ground-based analysis by science and engineering teams, machine learning algorithms could enhance the science return of these missions through development of autonomous science capabilities. Examples of science autonomy include onboard data analysis and subsequent instrument optimization, data prioritization (for transmission), and real-time decision-making based on data analysis. Similar advances could be made to develop streamlined data processing software for rapid ground-based analyses. Here we discuss several ways machine learning and autonomy could be used for astrobiology missions, including landing site selection, prioritization and targeting of samples, classification of "features" (e.g., proposed biosignatures) and novelties (uncharacterized, "new" features, which may be of most interest to agnostic astrobiological investigations), and data transmission.
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Affiliation(s)
| | - Luoth Chou
- NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
- Georgetown University, Washington, DC, USA
| | - Victoria Da Poian
- NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
- Microtell LLC, Greenbelt, Maryland, USA
| | | | | | - Ricardo Arevalo
- Department of Geology, University of Maryland, College Park, Maryland, USA
| | - Marc Neveu
- NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
- Center for Research and Exploration in Space Sciences and Technology II (CRESST II), USA
- Department of Astronomy, University of Maryland, College Park, Maryland, USA
| | - Ziqin Ni
- Department of Geology, University of Maryland, College Park, Maryland, USA
| | - Heather Graham
- NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
| | - Jamie Elsila
- NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
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3
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Abstract
Data analysis methods have scarcely kept pace with the rapid increase in Earth observations, spurring the development of novel algorithms, storage methods, and computational techniques. For scientists interested in Mars, the problem is always the same: there is simultaneously never enough of the right data and an overwhelming amount of data in total. Finding sufficient data needles in a haystack to test a hypothesis requires hours of manual data screening, and more needles and hay are added constantly. To date, the vast majority of Martian research has been focused on either one-off local/regional studies or on hugely time-consuming manual global studies. Machine learning in its numerous forms can be helpful for future such work. Machine learning has the potential to help map and classify a large variety of both features and properties on the surface of Mars and to aid in the planning and execution of future missions. Here, we outline the current extent of machine learning as applied to Mars, summarize why machine learning should be an important tool for planetary geomorphology in particular, and suggest numerous research avenues and funding priorities for future efforts. We conclude that: (1) moving toward methods that require less human input (i.e., self- or semi-supervised) is an important paradigm shift for Martian applications, (2) new robust methods using generative adversarial networks to generate synthetic high-resolution digital terrain models represent an exciting new avenue for Martian geomorphologists, (3) more effort and money must be directed toward developing standardized datasets and benchmark tests, and (4) the community needs a large-scale, generalized, and programmatically accessible geographic information system (GIS).
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4
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Vasavada AR. Mission Overview and Scientific Contributions from the Mars Science Laboratory Curiosity Rover After Eight Years of Surface Operations. SPACE SCIENCE REVIEWS 2022; 218:14. [PMID: 35399614 PMCID: PMC8981195 DOI: 10.1007/s11214-022-00882-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Accepted: 03/21/2022] [Indexed: 06/14/2023]
Abstract
UNLABELLED NASA's Mars Science Laboratory mission, with its Curiosity rover, has been exploring Gale crater (5.4° S, 137.8° E) since 2012 with the goal of assessing the potential of Mars to support life. The mission has compiled compelling evidence that the crater basin accumulated sediment transported by marginal rivers into lakes that likely persisted for millions of years approximately 3.6 Ga ago in the early Hesperian. Geochemical and mineralogical assessments indicate that environmental conditions within this timeframe would have been suitable for sustaining life, if it ever were present. Fluids simultaneously circulated in the subsurface and likely existed through the dry phases of lake bed exposure and aeolian deposition, conceivably creating a continuously habitable subsurface environment that persisted to less than 3 Ga in the early Amazonian. A diversity of organic molecules has been preserved, though degraded, with evidence for more complex precursors. Solid samples show highly variable isotopic abundances of sulfur, chlorine, and carbon. In situ studies of modern wind-driven sediment transport and multiple large and active aeolian deposits have led to advances in understanding bedform development and the initiation of saltation. Investigation of the modern atmosphere and environment has improved constraints on the timing and magnitude of atmospheric loss, revealed the presence of methane and the crater's influence on local meteorology, and provided measurements of high-energy radiation at Mars' surface in preparation for future crewed missions. Rover systems and science instruments remain capable of addressing all key scientific objectives. Emphases on advance planning, flexibility, operations support work, and team culture have allowed the mission team to maintain a high level of productivity in spite of declining rover power and funding. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s11214-022-00882-7.
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Affiliation(s)
- Ashwin R. Vasavada
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA USA
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5
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Ding L, Zhou R, Yuan Y, Yang H, Li J, Yu T, Liu C, Wang J, Li S, Gao H, Deng Z, Li N, Wang Z, Gong Z, Liu G, Xie J, Wang S, Rong Z, Deng D, Wang X, Han S, Wan W, Richter L, Huang L, Gou S, Liu Z, Yu H, Jia Y, Chen B, Dang Z, Zhang K, Li L, He X, Liu S, Di K. A 2-year locomotive exploration and scientific investigation of the lunar farside by the Yutu-2 rover. Sci Robot 2022; 7:eabj6660. [PMID: 35044796 DOI: 10.1126/scirobotics.abj6660] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
The lunar nearside has been investigated by many uncrewed and crewed missions, but the farside of the Moon remains poorly known. Lunar farside exploration is challenging because maneuvering rovers with efficient locomotion in harsh extraterrestrial environment is necessary to explore geological characteristics of scientific interest. Chang'E-4 mission successfully targeted the Moon's farside and deployed a teleoperated rover (Yutu-2) to explore inside the Von Kármán crater, conveying rich information regarding regolith, craters, and rocks. Here, we report mobile exploration on the lunar farside with Yutu-2 over the initial 2 years. During its journey, Yutu-2 has experienced varying degrees of mild slip and skid, indicating that the terrain is relatively flat at large scales but scattered with local gentle slopes. Cloddy soil sticking on its wheels implies a greater cohesion of the lunar soil than encountered at other lunar landing sites. Further identification results indicate that the regolith resembles dry sand and sandy loam on Earth in bearing properties, demonstrating greater bearing strength than that identified during the Apollo missions. In sharp contrast to the sparsity of rocks along the traverse route, small fresh craters with unilateral moldable ejecta are abundant, and some of them contain high-reflectance materials at the bottom, suggestive of secondary impact events. These findings hint at notable differences in the surface geology between the lunar farside and nearside. Experience gained with Yutu-2 improves the understanding of the farside of the Moon, which, in return, may lead to locomotion with improved efficiency and larger range.
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Affiliation(s)
- L Ding
- State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150080, China
| | - R Zhou
- State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150080, China
| | - Y Yuan
- State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150080, China
| | - H Yang
- State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150080, China
| | - J Li
- Beijing Aerospace Control Center, Beijing 100094, China
| | - T Yu
- Beijing Aerospace Control Center, Beijing 100094, China
| | - C Liu
- Beijing Aerospace Control Center, Beijing 100094, China.,Key Laboratory of Science and Technology on Aerospace Flight Dynamics, Beijing 100094, China
| | - J Wang
- Beijing Aerospace Control Center, Beijing 100094, China
| | - S Li
- State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150080, China
| | - H Gao
- State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150080, China
| | - Z Deng
- State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150080, China
| | - N Li
- State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150080, China
| | - Z Wang
- State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150080, China
| | - Z Gong
- State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150080, China
| | - G Liu
- Department of Aerospace Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada
| | - J Xie
- Beijing Aerospace Control Center, Beijing 100094, China
| | - S Wang
- Beijing Aerospace Control Center, Beijing 100094, China
| | - Z Rong
- Beijing Aerospace Control Center, Beijing 100094, China
| | - D Deng
- Beijing Aerospace Control Center, Beijing 100094, China
| | - X Wang
- Beijing Aerospace Control Center, Beijing 100094, China.,Key Laboratory of Science and Technology on Aerospace Flight Dynamics, Beijing 100094, China
| | - S Han
- Beijing Aerospace Control Center, Beijing 100094, China
| | - W Wan
- State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
| | - L Richter
- Large Space Structures GmbH, Hauptstrasse 1, D-85386 Eching, Germany
| | - L Huang
- State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150080, China
| | - S Gou
- State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
| | - Z Liu
- State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150080, China
| | - H Yu
- State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150080, China
| | - Y Jia
- China Academy of Space Technology, Beijing 100094, China
| | - B Chen
- China Academy of Space Technology, Beijing 100094, China
| | - Z Dang
- China Academy of Space Technology, Beijing 100094, China
| | - K Zhang
- Beijing Aerospace Control Center, Beijing 100094, China
| | - L Li
- Beijing Aerospace Control Center, Beijing 100094, China
| | - X He
- Beijing Aerospace Control Center, Beijing 100094, China
| | - S Liu
- Beijing Aerospace Control Center, Beijing 100094, China
| | - K Di
- State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
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6
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Doyle R, Kubota T, Picard M, Sommer B, Ueno H, Visentin G, Volpe R. Recent research and development activities on space robotics and AI. Adv Robot 2021. [DOI: 10.1080/01691864.2021.1978861] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Richard Doyle
- The Information and Data Science Program Office, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Takashi Kubota
- Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency, Sagamihara Japan
| | - Martin Picard
- Space Exploration, Canadian Space Agency, Quebec, Canada
| | - Bernd Sommer
- Automation and Robotics, German Aerospace Center Bonn, Germany
| | - Hiroshi Ueno
- Business Development and Industrial Relations Department, Japan Aerospace Exploration Agency, Tokyo Japan
| | | | - Richard Volpe
- The Mobility and Robotic Systems Section, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
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7
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Mateo-Garcia G, Veitch-Michaelis J, Smith L, Oprea SV, Schumann G, Gal Y, Baydin AG, Backes D. Towards global flood mapping onboard low cost satellites with machine learning. Sci Rep 2021; 11:7249. [PMID: 33790368 PMCID: PMC8012608 DOI: 10.1038/s41598-021-86650-z] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Accepted: 03/04/2021] [Indexed: 11/09/2022] Open
Abstract
Spaceborne Earth observation is a key technology for flood response, offering valuable information to decision makers on the ground. Very large constellations of small, nano satellites- 'CubeSats' are a promising solution to reduce revisit time in disaster areas from days to hours. However, data transmission to ground receivers is limited by constraints on power and bandwidth of CubeSats. Onboard processing offers a solution to decrease the amount of data to transmit by reducing large sensor images to smaller data products. The ESA's recent PhiSat-1 mission aims to facilitate the demonstration of this concept, providing the hardware capability to perform onboard processing by including a power-constrained machine learning accelerator and the software to run custom applications. This work demonstrates a flood segmentation algorithm that produces flood masks to be transmitted instead of the raw images, while running efficiently on the accelerator aboard the PhiSat-1. Our models are trained on WorldFloods: a newly compiled dataset of 119 globally verified flooding events from disaster response organizations, which we make available in a common format. We test the system on independent locations, demonstrating that it produces fast and accurate segmentation masks on the hardware accelerator, acting as a proof of concept for this approach.
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Affiliation(s)
| | | | | | | | - Guy Schumann
- University of Bristol, Bristol, UK
- RSS-Hydro, RED, Dudelange, Luxembourg
| | | | | | - Dietmar Backes
- University of Luxembourg, Luxembourg, Luxembourg
- University College London, London, UK
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8
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Bampis L, Gasteratos A, Boukas E. CNN‐based novelty detection for terrestrial and extra‐terrestrial autonomous exploration. IET CYBER-SYSTEMS AND ROBOTICS 2021. [DOI: 10.1049/csy2.12013] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Affiliation(s)
- Loukas Bampis
- Department of Production and Management Engineering Democritus University of Thrace Xanthi Greece
| | - Antonios Gasteratos
- Department of Production and Management Engineering Democritus University of Thrace Xanthi Greece
| | - Evangelos Boukas
- Department of Electrical Engineering Technical University of Denmark Kongens Lyngby Denmark
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9
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Wiens RC, Maurice S, Robinson SH, Nelson AE, Cais P, Bernardi P, Newell RT, Clegg S, Sharma SK, Storms S, Deming J, Beckman D, Ollila AM, Gasnault O, Anderson RB, André Y, Michael Angel S, Arana G, Auden E, Beck P, Becker J, Benzerara K, Bernard S, Beyssac O, Borges L, Bousquet B, Boyd K, Caffrey M, Carlson J, Castro K, Celis J, Chide B, Clark K, Cloutis E, Cordoba EC, Cousin A, Dale M, Deflores L, Delapp D, Deleuze M, Dirmyer M, Donny C, Dromart G, George Duran M, Egan M, Ervin J, Fabre C, Fau A, Fischer W, Forni O, Fouchet T, Fresquez R, Frydenvang J, Gasway D, Gontijo I, Grotzinger J, Jacob X, Jacquinod S, Johnson JR, Klisiewicz RA, Lake J, Lanza N, Laserna J, Lasue J, Le Mouélic S, Legett C, Leveille R, Lewin E, Lopez-Reyes G, Lorenz R, Lorigny E, Love SP, Lucero B, Madariaga JM, Madsen M, Madsen S, Mangold N, Manrique JA, Martinez JP, Martinez-Frias J, McCabe KP, McConnochie TH, McGlown JM, McLennan SM, Melikechi N, Meslin PY, Michel JM, Mimoun D, Misra A, Montagnac G, Montmessin F, Mousset V, Murdoch N, Newsom H, Ott LA, Ousnamer ZR, Pares L, Parot Y, Pawluczyk R, Glen Peterson C, Pilleri P, Pinet P, Pont G, Poulet F, Provost C, Quertier B, Quinn H, Rapin W, Reess JM, Regan AH, Reyes-Newell AL, Romano PJ, Royer C, Rull F, Sandoval B, Sarrao JH, Sautter V, Schoppers MJ, Schröder S, Seitz D, Shepherd T, Sobron P, Dubois B, Sridhar V, Toplis MJ, Torre-Fdez I, Trettel IA, Underwood M, Valdez A, Valdez J, Venhaus D, Willis P. The SuperCam Instrument Suite on the NASA Mars 2020 Rover: Body Unit and Combined System Tests. SPACE SCIENCE REVIEWS 2021; 217:4. [PMID: 33380752 PMCID: PMC7752893 DOI: 10.1007/s11214-020-00777-5] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Accepted: 11/27/2020] [Indexed: 05/16/2023]
Abstract
The SuperCam instrument suite provides the Mars 2020 rover, Perseverance, with a number of versatile remote-sensing techniques that can be used at long distance as well as within the robotic-arm workspace. These include laser-induced breakdown spectroscopy (LIBS), remote time-resolved Raman and luminescence spectroscopies, and visible and infrared (VISIR; separately referred to as VIS and IR) reflectance spectroscopy. A remote micro-imager (RMI) provides high-resolution color context imaging, and a microphone can be used as a stand-alone tool for environmental studies or to determine physical properties of rocks and soils from shock waves of laser-produced plasmas. SuperCam is built in three parts: The mast unit (MU), consisting of the laser, telescope, RMI, IR spectrometer, and associated electronics, is described in a companion paper. The on-board calibration targets are described in another companion paper. Here we describe SuperCam's body unit (BU) and testing of the integrated instrument. The BU, mounted inside the rover body, receives light from the MU via a 5.8 m optical fiber. The light is split into three wavelength bands by a demultiplexer, and is routed via fiber bundles to three optical spectrometers, two of which (UV and violet; 245-340 and 385-465 nm) are crossed Czerny-Turner reflection spectrometers, nearly identical to their counterparts on ChemCam. The third is a high-efficiency transmission spectrometer containing an optical intensifier capable of gating exposures to 100 ns or longer, with variable delay times relative to the laser pulse. This spectrometer covers 535-853 nm ( 105 - 7070 cm - 1 Raman shift relative to the 532 nm green laser beam) with 12 cm - 1 full-width at half-maximum peak resolution in the Raman fingerprint region. The BU electronics boards interface with the rover and control the instrument, returning data to the rover. Thermal systems maintain a warm temperature during cruise to Mars to avoid contamination on the optics, and cool the detectors during operations on Mars. Results obtained with the integrated instrument demonstrate its capabilities for LIBS, for which a library of 332 standards was developed. Examples of Raman and VISIR spectroscopy are shown, demonstrating clear mineral identification with both techniques. Luminescence spectra demonstrate the utility of having both spectral and temporal dimensions. Finally, RMI and microphone tests on the rover demonstrate the capabilities of these subsystems as well.
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Affiliation(s)
| | - Sylvestre Maurice
- Institut de Recherche en Astrophysique et Planetologie (IRAP), Université de Toulouse, UPS, CNRS, Toulouse, France
| | | | | | - Philippe Cais
- Laboratoire d’astrophysique de Bordeaux, Univ. Bordeaux, CNRS, Bordeaux, France
| | - Pernelle Bernardi
- Laboratoire d’Etudes Spatiales et d’Instrumentation en Astrophysique, Observatoire de Paris, Meudon, France
| | | | - Sam Clegg
- Los Alamos National Laboratory, Los Alamos, NM USA
| | | | | | | | | | | | - Olivier Gasnault
- Institut de Recherche en Astrophysique et Planetologie (IRAP), Université de Toulouse, UPS, CNRS, Toulouse, France
| | - Ryan B. Anderson
- U.S. Geological Survey Astrogeology Science Center, Flagstaff, AZ USA
| | - Yves André
- Centre National d’Etudes Spatiales, Toulouse, France
| | | | - Gorka Arana
- University of Basque Country, UPV/EHU, Bilbao, Spain
| | | | - Pierre Beck
- Institut de Planétologie et d’Astrophysique de Grenoble, Université Grenoble Alpes, Grenoble, France
| | | | - Karim Benzerara
- Institut de Minéralogie, Physique des Matériaux et Cosmochimie, CNRS, Museum National d’Histoire Naturelle, Sorbonne Université, Paris, France
| | - Sylvain Bernard
- Institut de Minéralogie, Physique des Matériaux et Cosmochimie, CNRS, Museum National d’Histoire Naturelle, Sorbonne Université, Paris, France
| | - Olivier Beyssac
- Institut de Minéralogie, Physique des Matériaux et Cosmochimie, CNRS, Museum National d’Histoire Naturelle, Sorbonne Université, Paris, France
| | - Louis Borges
- Los Alamos National Laboratory, Los Alamos, NM USA
| | - Bruno Bousquet
- Centre Lasers Intenses et Applications, University of Bordeaux, Bordeaux, France
| | - Kerry Boyd
- Los Alamos National Laboratory, Los Alamos, NM USA
| | | | | | - Kepa Castro
- University of Basque Country, UPV/EHU, Bilbao, Spain
| | - Jorden Celis
- Los Alamos National Laboratory, Los Alamos, NM USA
| | - Baptiste Chide
- Institut de Recherche en Astrophysique et Planetologie (IRAP), Université de Toulouse, UPS, CNRS, Toulouse, France
- Institut Supérieur de l’Aéronautique et de l’Espace (ISAE), Toulouse, France
| | - Kevin Clark
- Jet Propulsion Laboratory/Caltech, Pasadena, CA USA
| | | | | | - Agnes Cousin
- Institut de Recherche en Astrophysique et Planetologie (IRAP), Université de Toulouse, UPS, CNRS, Toulouse, France
| | | | | | | | | | | | | | - Gilles Dromart
- Univ Lyon, ENSL, Univ Lyon 1, CNRS, LGL-TPE, 69364 Lyon, France
| | | | | | - Joan Ervin
- Jet Propulsion Laboratory/Caltech, Pasadena, CA USA
| | - Cecile Fabre
- GeoRessources, Université de Lorraine, Nancy, France
| | - Amaury Fau
- Institut de Minéralogie, Physique des Matériaux et Cosmochimie, CNRS, Museum National d’Histoire Naturelle, Sorbonne Université, Paris, France
| | | | - Olivier Forni
- Institut de Recherche en Astrophysique et Planetologie (IRAP), Université de Toulouse, UPS, CNRS, Toulouse, France
| | - Thierry Fouchet
- Laboratoire d’Etudes Spatiales et d’Instrumentation en Astrophysique, Observatoire de Paris, Meudon, France
| | | | | | | | | | | | - Xavier Jacob
- Institut de mécanique des fluides de Toulouse (CNRS, INP, Univ. Toulouse), Toulouse, France
| | - Sophie Jacquinod
- Laboratoire d’Etudes Spatiales et d’Instrumentation en Astrophysique, Observatoire de Paris, Meudon, France
| | | | | | - James Lake
- Los Alamos National Laboratory, Los Alamos, NM USA
| | - Nina Lanza
- Los Alamos National Laboratory, Los Alamos, NM USA
| | | | - Jeremie Lasue
- Institut de Recherche en Astrophysique et Planetologie (IRAP), Université de Toulouse, UPS, CNRS, Toulouse, France
| | - Stéphane Le Mouélic
- Laboratoire de Planétologie et Géodynamique, Université de Nantes, Université d’Angers, CNRS UMR 6112, Nantes, France
| | - Carey Legett
- Los Alamos National Laboratory, Los Alamos, NM USA
| | | | - Eric Lewin
- Institut de Planétologie et d’Astrophysique de Grenoble, Université Grenoble Alpes, Grenoble, France
| | | | - Ralph Lorenz
- Johns Hopkins University Applied Physics Laboratory, Laurel, MD USA
| | - Eric Lorigny
- Centre National d’Etudes Spatiales, Toulouse, France
| | | | | | | | | | - Soren Madsen
- Jet Propulsion Laboratory/Caltech, Pasadena, CA USA
| | - Nicolas Mangold
- Laboratoire de Planétologie et Géodynamique, Université de Nantes, Université d’Angers, CNRS UMR 6112, Nantes, France
| | | | | | | | | | | | | | | | | | - Pierre-Yves Meslin
- Institut de Recherche en Astrophysique et Planetologie (IRAP), Université de Toulouse, UPS, CNRS, Toulouse, France
| | | | - David Mimoun
- Institut Supérieur de l’Aéronautique et de l’Espace (ISAE), Toulouse, France
| | | | | | - Franck Montmessin
- Laboratoire Atmosphères, Milieux, Observations Spatiales, Paris, France
| | | | - Naomi Murdoch
- Institut Supérieur de l’Aéronautique et de l’Espace (ISAE), Toulouse, France
| | | | - Logan A. Ott
- Los Alamos National Laboratory, Los Alamos, NM USA
| | | | - Laurent Pares
- Institut de Recherche en Astrophysique et Planetologie (IRAP), Université de Toulouse, UPS, CNRS, Toulouse, France
| | - Yann Parot
- Institut de Recherche en Astrophysique et Planetologie (IRAP), Université de Toulouse, UPS, CNRS, Toulouse, France
| | | | | | - Paolo Pilleri
- Institut de Recherche en Astrophysique et Planetologie (IRAP), Université de Toulouse, UPS, CNRS, Toulouse, France
| | - Patrick Pinet
- Institut de Recherche en Astrophysique et Planetologie (IRAP), Université de Toulouse, UPS, CNRS, Toulouse, France
| | - Gabriel Pont
- Centre National d’Etudes Spatiales, Toulouse, France
| | | | | | - Benjamin Quertier
- Laboratoire d’astrophysique de Bordeaux, Univ. Bordeaux, CNRS, Bordeaux, France
| | | | - William Rapin
- Institut de Minéralogie, Physique des Matériaux et Cosmochimie, CNRS, Museum National d’Histoire Naturelle, Sorbonne Université, Paris, France
| | - Jean-Michel Reess
- Laboratoire d’Etudes Spatiales et d’Instrumentation en Astrophysique, Observatoire de Paris, Meudon, France
| | - Amy H. Regan
- Los Alamos National Laboratory, Los Alamos, NM USA
| | | | | | - Clement Royer
- Institut d’Astrophysique Spatiale (IAS), Orsay, France
| | | | | | | | - Violaine Sautter
- Institut de Minéralogie, Physique des Matériaux et Cosmochimie, CNRS, Museum National d’Histoire Naturelle, Sorbonne Université, Paris, France
| | | | - Susanne Schröder
- Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institute of Optical Sensor Systems, Berlin, Germany
| | - Daniel Seitz
- Los Alamos National Laboratory, Los Alamos, NM USA
| | | | | | - Bruno Dubois
- Université de Toulouse; UPS-OMP, Toulouse, France
| | | | - Michael J. Toplis
- Institut de Recherche en Astrophysique et Planetologie (IRAP), Université de Toulouse, UPS, CNRS, Toulouse, France
| | | | | | | | | | - Jacob Valdez
- Los Alamos National Laboratory, Los Alamos, NM USA
| | - Dawn Venhaus
- Los Alamos National Laboratory, Los Alamos, NM USA
| | - Peter Willis
- Jet Propulsion Laboratory/Caltech, Pasadena, CA USA
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10
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Wiens RC, Edgett KS, Stack KM, Dietrich WE, Bryk AB, Mangold N, Bedford C, Gasda P, Fairen A, Thompson L, Johnson J, Gasnault O, Clegg S, Cousin A, Forni O, Frydenvang J, Lanza N, Maurice S, Newsom H, Ollila A, Payré V, Rivera-Hernandez F, Vasavada A. Origin and composition of three heterolithic boulder- and cobble-bearing deposits overlying the Murray and Stimson formations, Gale Crater, Mars. ICARUS 2020; 350:113897. [PMID: 32606479 PMCID: PMC7326610 DOI: 10.1016/j.icarus.2020.113897] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Heterolithic, boulder-containing, pebble-strewn surfaces occur along the lower slopes of Aeolis Mons ("Mt. Sharp") in Gale crater, Mars. They were observed in HiRISE images acquired from orbit prior to the landing of the Curiosity rover. The rover was used to investigate three of these units named Blackfoot, Brandberg, and Bimbe between sols 1099 and 1410. These unconsolidated units overlie the lower Murray formation that forms the base of Mt. Sharp, and consist of pebbles, cobbles and boulders. Blackfoot also overlies portions of the Stimson formation, which consists of eolian sandstone that is understood to significantly postdate the dominantly lacustrine deposition of the Murray formation. Blackfoot is elliptical in shape (62 × 26 m), while Brandberg is nearly circular (50 × 55 m), and Bimbe is irregular in shape, covering about ten times the area of the other two. The largest boulders are 1.5-2.5 m in size and are interpreted to be sandstones. As seen from orbit, some boulders are light-toned and others are dark-toned. Rover-based observations show that both have the same gray appearance from the ground and their apparently different albedos in orbital observations result from relatively flat sky-facing surfaces. Chemical observations show that two clasts of fine sandstone at Bimbe have similar compositions and morphologies to nine ChemCam targets observed early in the mission, near Yellowknife Bay, including the Bathurst Inlet outcrop, and to at least one target (Pyramid Hills, Sol 692) and possibly a cap rock unit just north of Hidden Valley, locations that are several kilometers apart in distance and tens of meters in elevation. These findings may suggest the earlier existence of draping strata, like the Stimson formation, that would have overlain the current surface from Bimbe to Yellowknife Bay. Compositionally these extinct strata could be related to the Siccar Point group to which the Stimson formation belongs. Dark, massive sandstone blocks at Bimbe are chemically distinct from blocks of similar morphology at Bradbury Rise, except for a single float block, Oscar (Sol 516). Conglomerates observed along a low, sinuous ridge at Bimbe consist of matrix and clasts with compositions similar to the Stimson formation, suggesting that stream beds likely existed nearly contemporaneously with the dunes that eventually formed the Stimson formation, or that they had the same source material. In either case, they represent a later pulse of fluvial activity relative to the lakes associated with the Murray formation. These three units may be local remnants of infilled impact craters (especially circular-shaped Brandberg), decayed buttes, patches of unconsolidated fluvial deposits, or residual mass-movement debris. Their incorporation of Stimson and Murray rocks, the lack of lithification, and appearance of being erosional remnants suggest that they record erosion and deposition events that post-date the exposure of the Stimson formation.
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Affiliation(s)
| | | | - Kathryn M. Stack
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - William E. Dietrich
- Department of Earth and Planetary Science, University of California–Berkeley, Berkeley, CA, USA
| | - Alexander B. Bryk
- Department of Earth and Planetary Science, University of California–Berkeley, Berkeley, CA, USA
| | - Nicolas Mangold
- Laboratoire de Planétologie et Géodynamique, UMR 6112 CNRS, Université Nantes, Université d’Angers, Nantes, France
| | | | | | - Alberto Fairen
- Centro de Astrobiologia (CSIC-INTA), Madrid, Spain
- Department of Astronomy, Cornell University, Ithaca, NY, USA
| | - Lucy Thompson
- Planetary and Space Science Centre, University of New Brunswick, Fredericton, New Brunswick, Canada
| | - Jeff Johnson
- Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA
| | - Olivier Gasnault
- Université de Toulouse, UPS-OMP, Toulouse, France
- Institut de Recherche en Astrophysique et Planéetologie, CNRS, UMR 5277, Toulouse, France
| | - Sam Clegg
- Los Alamos National Laboratory, Los Alamos, NM, USA
| | - Agnes Cousin
- Université de Toulouse, UPS-OMP, Toulouse, France
- Institut de Recherche en Astrophysique et Planéetologie, CNRS, UMR 5277, Toulouse, France
| | - Olivier Forni
- Université de Toulouse, UPS-OMP, Toulouse, France
- Institut de Recherche en Astrophysique et Planéetologie, CNRS, UMR 5277, Toulouse, France
| | | | - Nina Lanza
- Los Alamos National Laboratory, Los Alamos, NM, USA
| | - Sylvestre Maurice
- Université de Toulouse, UPS-OMP, Toulouse, France
- Institut de Recherche en Astrophysique et Planéetologie, CNRS, UMR 5277, Toulouse, France
| | - Horton Newsom
- Institute of Meteoritics, University of New Mexico, Albuquerque, NM, USA
| | - Ann Ollila
- Los Alamos National Laboratory, Los Alamos, NM, USA
| | - Valerie Payré
- Earth, Environmental, and Planetary Sciences, Rice University, Houston, TX, USA
| | | | - Ashwin Vasavada
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
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11
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Gaines D, Doran G, Paton M, Rothrock B, Russino J, Mackey R, Anderson R, Francis R, Joswig C, Justice H, Kolcio K, Rabideau G, Schaffer S, Sawoniewicz J, Vasavada A, Wong V, Yu K, Agha‐mohammadi A. Self‐reliant rovers for increased mission productivity. J FIELD ROBOT 2020. [DOI: 10.1002/rob.21979] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Daniel Gaines
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena California USA
| | - Gary Doran
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena California USA
| | - Michael Paton
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena California USA
| | - Brandon Rothrock
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena California USA
| | - Joseph Russino
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena California USA
| | - Ryan Mackey
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena California USA
| | - Robert Anderson
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena California USA
| | - Raymond Francis
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena California USA
| | - Chet Joswig
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena California USA
| | - Heather Justice
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena California USA
| | | | - Gregg Rabideau
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena California USA
| | - Steve Schaffer
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena California USA
| | - Jacek Sawoniewicz
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena California USA
| | - Ashwin Vasavada
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena California USA
| | - Vincent Wong
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena California USA
| | - Kathryn Yu
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena California USA
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12
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Aguzzi J, Flexas MM, Flögel S, Lo Iacono C, Tangherlini M, Costa C, Marini S, Bahamon N, Martini S, Fanelli E, Danovaro R, Stefanni S, Thomsen L, Riccobene G, Hildebrandt M, Masmitja I, Del Rio J, Clark EB, Branch A, Weiss P, Klesh AT, Schodlok MP. Exo-Ocean Exploration with Deep-Sea Sensor and Platform Technologies. ASTROBIOLOGY 2020; 20:897-915. [PMID: 32267735 DOI: 10.1089/ast.2019.2129] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
One of Saturn's largest moons, Enceladus, possesses a vast extraterrestrial ocean (i.e., exo-ocean) that is increasingly becoming the hotspot of future research initiatives dedicated to the exploration of putative life. Here, a new bio-exploration concept design for Enceladus' exo-ocean is proposed, focusing on the potential presence of organisms across a wide range of sizes (i.e., from uni- to multicellular and animal-like), according to state-of-the-art sensor and robotic platform technologies used in terrestrial deep-sea research. In particular, we focus on combined direct and indirect life-detection capabilities, based on optoacoustic imaging and passive acoustics, as well as molecular approaches. Such biologically oriented sampling can be accompanied by concomitant geochemical and oceanographic measurements to provide data relevant to exo-ocean exploration and understanding. Finally, we describe how this multidisciplinary monitoring approach is currently enabled in terrestrial oceans through cabled (fixed) observatories and their related mobile multiparametric platforms (i.e., Autonomous Underwater and Remotely Operated Vehicles, as well as crawlers, rovers, and biomimetic robots) and how their modified design can be used for exo-ocean exploration.
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Affiliation(s)
- J Aguzzi
- Instituto de Ciencias del Mar (ICM-CSIC), Barcelona, Spain
- Stazione Zoologica Anton Dohrn, Naples, Italy
| | - M M Flexas
- California Institute of Technology, Pasadena, California, USA
| | - S Flögel
- GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany
| | - C Lo Iacono
- Instituto de Ciencias del Mar (ICM-CSIC), Barcelona, Spain
- National Oceanographic Center (NOC), University of Southampton, Southampton, United Kingdom
| | | | - C Costa
- Consiglio per la ricerca in agricoltura e l'analisi dell'economia agraria (CREA)-Centro di ricerca Ingegneria e Trasformazioni agroalimentari - Monterotondo, Rome, Italy
| | - S Marini
- Stazione Zoologica Anton Dohrn, Naples, Italy
- National Research Council of Italy (CNR), Institute of Marine Sciences, La Spezia, Italy
| | - N Bahamon
- Instituto de Ciencias del Mar (ICM-CSIC), Barcelona, Spain
- Centro de Estudios Avanzados de Blanes (CEAB-CSIC), Blanes, Spain
| | - S Martini
- Sorbonne Université, CNRS, Laboratoire d'Océanographie de Villefranche, Villefranche-sur-mer, France
| | - E Fanelli
- Stazione Zoologica Anton Dohrn, Naples, Italy
- Department of Life and Environmental Sciences, Polytechnic University of Marche, Ancona, Italy
| | - R Danovaro
- Stazione Zoologica Anton Dohrn, Naples, Italy
- Department of Life and Environmental Sciences, Polytechnic University of Marche, Ancona, Italy
| | - S Stefanni
- Stazione Zoologica Anton Dohrn, Naples, Italy
| | | | - G Riccobene
- Istituto Nazionale di Fisica Nucleare (INFN), Laboratori Nazionali del Sud, Catania, Italy
| | - M Hildebrandt
- German Research Center for Artificial Intelligence (DFKI), Bremen, Germany
| | - I Masmitja
- SARTI, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain
| | - J Del Rio
- SARTI, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain
| | - E B Clark
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
| | - A Branch
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
| | | | - A T Klesh
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
| | - M P Schodlok
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
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13
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Kerner HR, Wagstaff KL, Bue BD, Wellington DF, Jacob S, Horton P, Bell JF, Kwan C, Ben Amor H. Comparison of novelty detection methods for multispectral images in rover-based planetary exploration missions. Data Min Knowl Discov 2020. [DOI: 10.1007/s10618-020-00697-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
Abstract
Science teams for rover-based planetary exploration missions like the Mars Science Laboratory Curiosity rover have limited time for analyzing new data before making decisions about follow-up observations. There is a need for systems that can rapidly and intelligently extract information from planetary instrument datasets and focus attention on the most promising or novel observations. Several novelty detection methods have been explored in prior work for three-channel color images and non-image datasets, but few have considered multispectral or hyperspectral image datasets for the purpose of scientific discovery. We compared the performance of four novelty detection methods—Reed Xiaoli (RX) detectors, principal component analysis (PCA), autoencoders, and generative adversarial networks (GANs)—and the ability of each method to provide explanatory visualizations to help scientists understand and trust predictions made by the system. We show that pixel-wise RX and autoencoders trained with structural similarity (SSIM) loss can detect morphological novelties that are not detected by PCA, GANs, and mean squared error autoencoders, but that the latter methods are better suited for detecting spectral novelties—i.e., the best method for a given setting depends on the type of novelties that are sought. Additionally, we find that autoencoders provide the most useful explanatory visualizations for enabling users to understand and trust model detections, and that existing GAN approaches to novelty detection may be limited in this respect.
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14
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Everybody Needs Somebody Sometimes: Validation of Adaptive Recovery in Robotic Space Operations. IEEE Robot Autom Lett 2019. [DOI: 10.1109/lra.2019.2894381] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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15
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Arora A, Furlong PM, Fitch R, Sukkarieh S, Fong T. Multi-modal active perception for information gathering in science missions. Auton Robots 2019. [DOI: 10.1007/s10514-019-09836-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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16
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Thompson DR, Candela A, Wettergreen DS, Dobrea EN, Swayze GA, Clark RN, Greenberger R. Spatial Spectroscopic Models for Remote Exploration. ASTROBIOLOGY 2018; 18:934-954. [PMID: 30035643 DOI: 10.1089/ast.2017.1782] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Ancient hydrothermal systems are a high-priority target for a future Mars sample return mission because they contain energy sources for microbes and can preserve organic materials (Farmer, 2000 ; MEPAG Next Decade Science Analysis Group, 2008 ; McLennan et al., 2012 ; Michalski et al., 2017 ). Characterizing these large, heterogeneous systems with a remote explorer is difficult due to communications bandwidth and latency; such a mission will require significant advances in spacecraft autonomy. Science autonomy uses intelligent sensor platforms that analyze data in real-time, setting measurement and downlink priorities to provide the best information toward investigation goals. Such automation must relate abstract science hypotheses to the measurable quantities available to the robot. This study captures these relationships by formalizing traditional "science traceability matrices" into probabilistic models. This permits experimental design techniques to optimize future measurements and maximize information value toward the investigation objectives, directing remote explorers that respond appropriately to new data. Such models are a rich new language for commanding informed robotic decision making in physically grounded terms. We apply these models to quantify the information content of different rover traverses providing profiling spectroscopy of Cuprite Hills, Nevada. We also develop two methods of representing spatial correlations using human-defined maps and remote sensing data. Model unit classifications are broadly consistent with prior maps of the site's alteration mineralogy, indicating that the model has successfully represented critical spatial and mineralogical relationships at Cuprite. Key Words: Autonomous science-Imaging spectroscopy-Alteration mineralogy-Field geology-Cuprite-AVIRIS-NG-Robotic exploration. Astrobiology 18, 934-954.
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Affiliation(s)
- David R Thompson
- 1 Jet Propulsion Laboratory, California Institute of Technology , Pasadena, California
| | - Alberto Candela
- 2 The Robotics Institute, Carnegie Mellon University , Pittsburgh, Pennsylvania
| | - David S Wettergreen
- 2 The Robotics Institute, Carnegie Mellon University , Pittsburgh, Pennsylvania
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17
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Shaik AK, Epuru NR, Syed H, Byram C, Soma VR. Femtosecond laser induced breakdown spectroscopy based standoff detection of explosives and discrimination using principal component analysis. OPTICS EXPRESS 2018; 26:8069-8083. [PMID: 29715780 DOI: 10.1364/oe.26.008069] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2018] [Accepted: 03/08/2018] [Indexed: 06/08/2023]
Abstract
We report the standoff (up to ~2 m) and remote (~8.5 m) detection of novel high energy materials/explosive molecules (Nitroimidazoles and Nitropyrazoles) using the technique of femtosecond laser induced breakdown spectroscopy (LIBS). We utilized two different collection systems (a) ME-OCT-0007 (commercially available) and (b) Schmidt-Cassegrain telescope for these experiments. In conjunction with LIBS data, principal component analysis was employed to discriminate/classify the explosives and the obtained results in both configurations are compared. Different aspects influencing the LIBS signal strength at far distances such as fluence at target, efficiency of collection system etc. are discussed.
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18
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Gao Y, Chien S. Review on space robotics: Toward top-level science through space exploration. Sci Robot 2017; 2:2/7/eaan5074. [DOI: 10.1126/scirobotics.aan5074] [Citation(s) in RCA: 87] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2017] [Accepted: 06/07/2017] [Indexed: 11/02/2022]
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19
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Jacobstein N, Bellingham J, Yang GZ. Robotics for space and marine sciences. Sci Robot 2017; 2:2/7/eaan5594. [PMID: 33157902 DOI: 10.1126/scirobotics.aan5594] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2017] [Accepted: 06/12/2017] [Indexed: 11/02/2022]
Affiliation(s)
- Neil Jacobstein
- Neil Jacobstein is the Chair of Artificial Intelligence and Robotics at Singularity University, NASA Research Park, Moffett Field, CA 94035, USA, and Distinguished Visiting Scholar, mediaX Program, Stanford University, Stanford, CA 94305, USA.,James Bellingham is the Director of the Center for Marine Robotics, Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA.,Guang-Zhong Yang is the Editor of Science Robotics and the Director of the Hamlyn Centre for Robotic Surgery, Imperial College London, London, UK.
| | - James Bellingham
- Neil Jacobstein is the Chair of Artificial Intelligence and Robotics at Singularity University, NASA Research Park, Moffett Field, CA 94035, USA, and Distinguished Visiting Scholar, mediaX Program, Stanford University, Stanford, CA 94305, USA.,James Bellingham is the Director of the Center for Marine Robotics, Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA.,Guang-Zhong Yang is the Editor of Science Robotics and the Director of the Hamlyn Centre for Robotic Surgery, Imperial College London, London, UK.
| | - Guang-Zhong Yang
- Neil Jacobstein is the Chair of Artificial Intelligence and Robotics at Singularity University, NASA Research Park, Moffett Field, CA 94035, USA, and Distinguished Visiting Scholar, mediaX Program, Stanford University, Stanford, CA 94305, USA.,James Bellingham is the Director of the Center for Marine Robotics, Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA.,Guang-Zhong Yang is the Editor of Science Robotics and the Director of the Hamlyn Centre for Robotic Surgery, Imperial College London, London, UK.
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20
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Chien S, Wagstaff KL. Robotic space exploration agents. Sci Robot 2017; 2:2/7/eaan4831. [DOI: 10.1126/scirobotics.aan4831] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2017] [Accepted: 05/11/2017] [Indexed: 11/02/2022]
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