Real-Life Cyborg Astrobiologists to Search for Signs of
Life on Future Mars Missions

post from The Daily Galaxy: Great Discoveries Channel on 03 November 2009 04:00:00 AM. © The Daily Galaxy: Great Discoveries Channel

At the remote Mars Desert Research Station in Utah, astronauts wearing artificial-intelligence enhanced spacesuits with digital eyes that can see in the infrared what human eyes are unable to see developed by Patrick McGuire (a University of Chicago geoscientist who?s developed algorithms that can recognize signs of life in a barren landscape) are testing future planetary rover missions that will travel long distances from their safe landing site to the exploration targets. The central nervous system of McGuire?s platform is a Hopfield neural network, a type of artificial intelligence that compares incoming data against patterns it?s seen before, eventually picking out those details that qualify as new or unusual.

For past few years, McGuire's team worked on CRISM, a Mars-orbiting imager that detects infrared and other invisible-to-human-eye wavelengths of light, allowing it to identify different types of rock and soil. McGuire envisions the digital eyes of cyborg astrobiologists as scaled-down versions of CRISM, their data perpetually crunched by the Hopfield networks on their hips.

In earlier efforts, the EuroGeo team developed a wearable-computer platform for testing computer-vision exploration algorithms in real-time at geological or astrobiological field sites, focusing on the concept of "uncommon mapping" in order to identify contrasting areas in an image of a planetary surface. Recently, the system was made more ergonomic and easy to use by porting the system into a phone-cam platform connected to a remote server.

The Mars Desert Research Station is the second such research station to be built, after the completion of the Arctic station (FMARS) on Devon Island in 2000. Stations to be built in Europe (Euro MARS) and Australia (MARS Oz) are currently in the planning stages.

The Cyborg Astrobiologist phone-cam platform, which utilizes the mobile-phone network, is now functional. New platforms will add a Bluetooth communications and a second computer-vision exploration algorithm using a neural network in order to remember aspects of previous images and to perform novelty detection. Future enhanncements to the Cyborg Astrobiologist system that will help identify both carbon and non-carbon forms of life will include:

1) Texture detection and recognition: Wth plans to implement a texture recognition algorithm to be able to discriminate between rocks with similar colors. This algorithm will both recognize textures it has seen in previous images and detect predefined structures characteristic of cert-ain rock types, such as layering.

2) Expand wavelength domain: The existing system is capable of treating multispectral images with further channels in the near infrared without major adaptations.

3) Processing speed: The system will benefit from an increase in processing and transmission speed from the current 120 sec/picture to 30 sec/picture.

The Cyborg Astrobiologist is the cuurent realization of the integration of man with with machine. Whoever said science is totally cool!

Casey Kazan

Source: The Cyborg Astrobiologist: Teaching Computers to Find Uncommon or Novel Areas of Geological Scenery in Real-time. http://geosci.uchicago.edu/~mcguire/Cyborg_ESLAB_2009.pdf