Stephen Williams and Ayanna M. Howard

Human-Automation Systems Lab

Georgia Institute of Technology

Evaluation of Visual Navigation Methods for Lunar Polar Rovers in Analogous Environments

Evaluation of Visual Navigation Methods for Lunar Polar Rovers in Analogous Environments

MotivationMotivation Recent lunar missions have focused on the

search for water ice near the poles LCROSS Clementine Lunar Prospector

On-orbit sensing still requires sensor measurement validation The only direct, unambiguous way is through

ground-based data However, there has never been a landed

mission to this region

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MotivationMotivation Earth-centric satellite sensing suffers from

similar issues Surface data validation even more critical due to

complex atmospheric effects Glacial regions are of particular importance

More sensitive to climate change mechanisms Poorly modeled by other observed surfaces Remote, harsh climate leads to few validation

trials

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SnoMote ProjectSnoMote Project Fixed weather stations do exist

in Greenland and Antarctica Sparse coverage of glacial surface

Scientists interested in the ability to collect dense measurements in targeted locations

This project focused on developing enabling technologies for a glacial mobile weather station

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SnoMote Sensor NodeSnoMote Sensor Node

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Mendenhall Glacier TestsMendenhall Glacier Tests

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EnvironmentEnvironment

Low contrast Slope-based hazards

Exposed mountain peaks Crevasse Blue ice

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Multi-agent ResearchMulti-agent Research Distributed Task Allocation (Antidio Viguria)

Fault tolerant Closer to the global optimal than standard

algorithms Embedded Graph Grammars (Brian Smith)

Enables nodes to self-assemble and maintain desired network topology

Accounts for the dynamics of the platform

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Visual NavigationVisual Navigation Terrain Assessment and Localization

Low contrast, snow-covered terrain

Methods for testing and evaluating through simulation

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Glacial Terrain Assessment

Glacial Terrain Assessment

Estimate the directionality of small-scale surface features within a small region

Based on methods used for Fingerprint Analysis

Determines the Least Squares Estimate of the dominate 2-D Fourier Spectrum direction

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Glacial Terrain Assessment

Glacial Terrain Assessment

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Glacial Visual SLAMGlacial Visual SLAM

Standard Visual SLAM system

Major Challenge – Feature Extraction Region Extraction Contrast

Enhancement SIFT Features

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Glacial Visual SLAMGlacial Visual SLAM

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Evaluation Using Simulation

Evaluation Using Simulation

Ground truth unknown for real environment Local scale terrain topology is unavailable Commodity GPS has significant uncertainty

Simulation system solves these issues Visual quality of simulation impacts the results of

visual algorithms

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Simulation DesignSimulation Design Presented work based on Gazebo open

source simulation system Real surface topologies used

SRTM data for terrestrial sites LRO data for lunar sites

Satellite imaging used to “paint” the terrain

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Simulation DesignSimulation Design Photo-realistic background applied using a

“skybox” Background images created from panorama of

test site Local scale texture blended with main terrain

coloration High frequency components extracted from

photography of test site

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Simulation DesignSimulation Design

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Assessing Simulation Quality

Assessing Simulation Quality

Easy to perform a qualitative comparison “That looks good…”

A method is needed to compare qualitatively

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Assessing Simulation Quality

Assessing Simulation Quality

Any visual algorithm may be applied to images from either simulation or the real terrain

A performance metric can be used to evaluate the effectiveness a specific algorithm

If the difference in performance results are not statistically significant, then the simulation may be viewed as sufficient

Must be evaluated on each algorithm-metric pair

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Assessing Simulation Quality

Assessing Simulation Quality

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Region Extraction Feature Count

ConclusionsConclusions Real-time vision-based processing techniques were

presented Implemented to cope with image characteristics of glacial

terrain Time and expense of field deployments in remote

regions prevent frequent trials Ground truth data difficult to obtain in real

environments Visually faithful simulation system developed to test

and validate vision-based algorithms Analysis conducted to assess the visual quality of the

simulation

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Future WorkFuture Work

Further testing and validation of simulation assessment method

Development of a simulated “science sensor” to enable testing of science-driven control behaviors Spatial and temporal data interpolation Include noise models

Opportunistic SnoMote testing in Anchorage, Alaska

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AcknowledgmentsAcknowledgments NASA Earth Science Technology Office

provided funding for this work under the Applied Information Systems Technology Program

Dr. Magnus Egerstedt, Georgia Institute of Technology, provided his experience in multi-agent formations

Dr. Matt Heavner, Associate Professor of Physics, University of Alaska Southeast, provided his expertise in glacial field work

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ReferencesReferences B. P. Gerkey, R. T. Vaughan, and A. Howard, “The Player/Stage project:

Tools for Multi-Robot and distributed sensor systems,” in International Conference on Advanced Robotics, ICAR, Coimbra, Portugal, July 2003, pp. 317–323.

L. Hong, Y. Wan, and A. Jain, “Fingerprint image enhancement: Algorithm and performance evaluation,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 20, no. 8, pp. 777–789, 1998.

A. M. Reza, “Realization of the contrast limited adaptive histogram equalization (CLAHE) for Real-Time image enhancement,” The Journal of VLSI Signal Processing, vol. 38, no. 1, pp. 35–44, 2004.

S. Williams and A. M. Howard, “A single camera terrain slope estimation technique for natural arctic environments,” in IEEE International Conference on Robotics and Automation, ICRA, Pasadena, CA, May 2008, pp. 2729–2734.

——, “Developing monocular visual pose estimation for arctic environments,” Journal of Field Robotics, vol. 27, no. 2, pp. 145–157, 2009.

——, “Towards visual arctic terrain assessment,” in International Conference on Field and Service Robotics, FSR, Cambridge, MA, July 2009

S. Williams, S. Remy, and A. M. Howard, “,” in American Institute of Aeronautics and Astronautics Conference Infotech @ Aerospace, Atlanta, GA, April 2010,

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