Cyborg Astrobiologist -- Basic Idea:

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# Cyborg Astrobiologist -- Basic Idea: - PowerPoint PPT Presentation

Cooccurence 2D Histogram for Saturation. Novelty Detection with the FamE (FamiliarityEnergy) Hopfield Neural Net (after R. Bogacz, U. Bristol) Compute: averages: &lt;H&gt;,&lt; S&gt;, &lt;I&gt; for each segment x = (&lt;H&gt;,&lt; S&gt;, &lt;I&gt; ) T If (Energy_Hopfield( x ) &lt; -N/4 then Novel = FALSE;

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Presentation Transcript

Cooccurence

2D Histogram

for Saturation

Novelty Detection with the

FamE (FamiliarityEnergy) Hopfield NeuralNet

(after R. Bogacz, U. Bristol)

Compute:

averages: <H>,< S>, <I> for each segment

x = (<H>,< S>, <I> )T

If (Energy_Hopfield( x ) < -N/4 then

Novel = FALSE;

Else {

Novel = TRUE;

Store Pattern x in Hopfield Net; }

Repeat for all segments;

Repeat for all incoming images;

Sat(pix[i][j+1])

Sat(pix[i][j])

Algorithm: Simple Uncommon Map

Simple Image

Uncommon Map

Brighter = “more uncommon”

(For the image on the left)

• “The Cyborg Astrobiologist:Teaching Computers to Find Uncommon or Novel Areas of Geological Scenery in Real-time”
• Network Conference of the Alexander von Humboldt Foundation, Muenster, Germany, November 2008.
• Authors: Patrick C. McGuire1,5,6,*, Enrique Díaz Martínez1,3, Jens Ormö1, Javier Gómez Elvíra1, Virginia Souza-Egipsy1, Helge Ritter2, Markus Oesker2, Robert Haschke2, Jörg Ontrup2, Florian Schmidt2, Alexandra Bartolo4, Richard Bose5, Lorenz Wendt6
• Institutions:
• 1Centro de Astrobiología (CAB, INTA/CSIC), Instituto Nacional Técnica Aeroespacial, Torrejón de Ardoz, Madrid, Spain: Robotics Laboratory, Planetary Geology Laboratory, Transdisciplinary Laboratory 2Universität Bielefeld, Germany, Neuroinformatics Group, Computer Science Department, Technische Fakultät 3(currently at) Dirreción de Geología y Geofísica, Instituto Geológico y Minero de España, Tres Cantos, Madrid, Spain 4Engineering Faculty, University of Malta, Malta 5McDonnell Center for the Space Sciences, Washington University, St. Louis, Missouri, USA 6Institute for Geosciences, Freie Universität Berlin, Department of Planetary Science and Remote Sensing, Berlin, Germany
• *(corresponding author) Email: mcguire@epsci.wustl.edu

McGuire, Ormöet al.,

Int’l Journal of Astrobiology

(2004)

McGuire, Diaz-Martinez et al.,

Int’l Journal of Astrobiology

(2005)

CONCEPT

Question: “Can an autonomous Robotic Astrobiologist someday be taught to understand a geological scene like the one pictured below?”

CyborgAstrobiologist -- Basic Idea:

Geologists’ intuition & high-level planning

Mission Riba1: Tripod Position “#2”,Inside the Cyborg Astrobiologist’s ‘Brain’

McGuire, Diaz-Martinez et al.,

Int’l Journal of Astrobiology

(2005)

Real-time Selection of Interest Points

Wearable Computer

Real-time Image-segmentation

VISION ALGORITHMS

Human Mobility

Video Camera, Firewire communication

(Cyborg Astrobiologist)++tested at Rivas Vaciamadrid (Sept 6, 2005)

Uncommonness

NoveltyDetection:CyborgAstrobiologistgets a memory (of Familiar patterns)

Uncommon

Map

Orig (Cam or Micro)

Full-color

Image Segmentation

Novel Segments

Cyborg Astrobiologist, with microscope, studying lichens

#1(Cam)

FIELD TESTS

Microscope in Field!

#18(Micro)

Lichen=White

Sporing = Red

Rock=Brown

Tripod!!

Not Yet

#19(Micro)

Lichen=White

Sporing = Red

Rock=Brown

Head-mounted Display failed in field 

Pictured here: tablet display

Not Yet

#23(Micro)

Lichen=

Algae + Fungus

(in Symbiosis)

Lichen = Black, Orange

Gypsum Crystal =

SmoothGray

Summary of Concept: Developing computer-vision technologies to automate some of a Human Geologist’s low-level thought processes. We are testing these computer vision technologies in the field in real-time with low-cost platforms, with the intention of later putting these algorithms on robotic platforms for exploring the Moon and Mars.

Currently working with collaborators in Madrid, Malta, St. Louis, Bielefeld and Berlin, in order to:

a) Do more comprehensive field tests at sites of geological and astrobiological interest using both the uncommon-map and novelty-detection systems.

b) Make the phone-cam system work with a field laptop enabled with Bluetooth, for automatic transfer of the images from the phone to the laptop and (marked- up) back to the phone. This should speed up the testing.

Future:0) Improved image-segmentation (to include texture) 1) Improved Novelty Detection (better statistical measures) 2) Improved cameras (hyperspectral cameras) 3) Improve technological readiness for planetary robotics missions.

The CyborgAstrobiologist:Ported from a wearable computer to the Astrobiology Phone-cam

Before:

HARDWARE IMPROVEMENTS

Now:

Bartolo, McGuire et al.,

International Journal of Astrobiology

(2007)