Rover traverse science for increased mission science return

Castafio, R.; Anderson, Robert C.; Estlin, Tara; DeCoste, Dennis; Fisher, Forest; Gaines, Daniel M.; Mazzoni, Dominic; Judd, M.

doi:10.1109/aero.2003.1235546

Cited by 22 publications

(25 citation statements)

References 7 publications

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“…Science opportunities can include detection of dust devils and clouds [6,7] and novel rocks that the rover has not seen before [3]. OASIS analyzes data the rover gathers, and then prioritizes the data based on criteria set by the science team.…”

Section: Introductionmentioning

confidence: 99%

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Onboard Autonomous Rover Science

Castaño

Estlin

Gaines

et al. 2007

2007 IEEE Aerospace Conference

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Abstract-The Onboard Autonomous Science Investigation System (OASIS) was used in the first formal demonstration of closed loop opportunistic detection and reaction during a rover traverse on the FIDO rover at NASA's Jet Propulsion Laboratory. In addition to hardware demonstrations, the system has been demonstrated and exercised in simulation using the Rover Analysis, Modeling, and Simulation (ROAMS) planetary rover simulator [1]. We discuss several system enhancements including new planning and scheduling capabilities and image prioritization. We also describe the new end-of-traverse capability that includes taking a partial panorama of images, assessing these for targets of interest, and collecting narrow angle images of selected targets. Finally, we present several methods for estimating properties of rocks and provide a comparative assessment. Understanding the relationship of these methods is important to correctly interpret autonomous rock analyses performed during a traverse.

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Section: Introductionmentioning

confidence: 99%

“…The capability we focus on in this work, onboard autonomous rover science, continues to grow in importance as rover lifetime and travel distances increase. OASIS [2][3][4][5][6], an Onboard Autonomous Science Investigation System, is a JPL-managed project designed to maximize mission science on rover missions with long traverses.…”

Section: Introductionmentioning

confidence: 99%

Onboard Autonomous Rover Science

Castaño

Estlin

Gaines

et al. 2007

2007 IEEE Aerospace Conference

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“…One key capability, autonomous onboard science, continues to grow in importance as rover travel distances continue to dramatically increase. OASIS [1,2], an Onboard Autonomous Science Investigation System, is a JPLmanaged project designed to maximize mission science on rover missions with long traverses.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper 1 , we provide a brief overview of the OASIS system, and then describe our recent successes in integrating with and using rover hardware. OASIS currently works in a closed loop fashion with onboard control software (e.g., navigation and vision) and has the ability to autonomously perform the following sequence of steps: analyze gray scale images to find rocks, extract the properties of the rocks, identify rocks of interest, retask the rover to take additional imagery of the identified target and then allow the rover to continue on its original mission.…”

mentioning

confidence: 99%

Current results from a rover science data analysis system

Castaño

Judd

Estlin

et al. 2005

2005 IEEE Aerospace Conference

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Abstract-The Onboard Autonomous Science Investigation System (OASIS) evaluates geologic data gathered by a planetary rover. This analysis is used to prioritize the data for transmission, so that the data with the highest science value is transmitted to Earth. In addition, the onboard analysis results are used to identify science opportunities. A planning and scheduling component of the system enables the rover to take advantage of the identified science opportunity. OASIS is a NASA-funded research project that is currently being tested on the FIDO rover at JPL for use on future missions.In this paper 1 , we provide a brief overview of the OASIS system, and then describe our recent successes in integrating with and using rover hardware. OASIS currently works in a closed loop fashion with onboard control software (e.g., navigation and vision) and has the ability to autonomously perform the following sequence of steps: analyze gray scale images to find rocks, extract the properties of the rocks, identify rocks of interest, retask the rover to take additional imagery of the identified target and then allow the rover to continue on its original mission.We also describe the early 2004 ground test validation of specific OASIS components on selected Mars Exploration Rover (MER) images. These components include the rockfinding algorithm, RockIT, and the rock size feature extraction code. Our team also developed the RockIT GUI, an interface that allows users to easily visualize and modify the rock-finder results. This interface has allowed us to conduct preliminary testing and validation of the rockfinder's performance.

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“…There has been only modest research into the potential for autonomous interpretation of sensor data to enhance the scientific value of a mission [e.g. 4,5,6,7]. The on-going projects at NASA's Ames Research Center were initiated to address this gap in autonomy technology research.…”

Section: Introductionmentioning

confidence: 99%

Essential autonomous science inference on rovers (EASIR)

Roush

2004 IEEE Aerospace Conference Proceedings (IEEE Cat. No.04TH8720)

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Abstract-Existing constraints on time, computational, and communication resources associated with Mars rover missions suggest on-board science evaluation of sensor data can contribute to decreasing human-directed operational planning, optimizing returned science data volumes, and recognition of unique or novel data. All of which act to increase the scientific return from a mission. Many different levels of science autonomy exist and each impacts the data collected and returned by, and activities of, rovers. Several computational algorithms, designed to recognize objects of interest to geologists and biologists, are discussed. Theralgorithms represent various functions that producing scientific opinions and several scenarios illustrate how the opinions can be used.

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Rover traverse science for increased mission science return

Cited by 22 publications

References 7 publications

Onboard Autonomous Rover Science

Onboard Autonomous Rover Science

Current results from a rover science data analysis system

Essential autonomous science inference on rovers (EASIR)

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