Autonomous Exploration

The University at Albany (SUNY) has highlighted Knuth’s research in a recent news piece.

UAlbany Professor Kevin Knuth with a robot built from LEGOs. (Photo Mark Schmidt)

Kevin Knuth has a laboratory in the physics department of the University at Albany that is filled with LEGOs. The bricks are relatively cheap and can be used to rapidly prototype a robot’s body. Knuth’s robots are being programmed to solve such problems as mapping complex terrain.

At UAlbany Day on Saturday, Oct. 25, he will give a demonstration on Robotics and Robotic Exploration in Life Sciences Room 143 at 10:45 a.m.

More here:
http://www.albany.edu/news/update_4522.shtml

Building instructions for the robot shown in the UAlbany article can be found on Brickengineer.com

Visit Robots Everywhere for a general blog on robotics news.

Dr. Kevin Knuth was recently invited to give a presentation titled “Intelligent Science Platforms” at the 2008 Conference on Intelligent Data Understanding (CIDU).  The meeting was held from September 9-10, 2008 at NASA Headquarters in Washington DC.  The presentation slides can be downloaded here, or on the CIDU web site.

The abstract follows:

Intelligent Science Platforms

Kevin H. Knuth
Departments of Physics and Informatics, University at Albany, Albany NY 12222
Autonomous Exploration Inc., Albany NY 12208

The exploration of space requires that we continue our dependence on remote scientific platforms. The continued success of the Mars Exploration Rovers highlights the great benefits of navigational autonomy. However, science operations continue to require a team of scientists to select the specific experiments to perform and to precisely guide sensor placement. While this works well on Mars, which has a communication delay ranging from 6.5 to 44 minutes, this model will be strained during future operations on Jupiter’s icy moons, and will most certainly break on future Saturnian missions to Titan and Enceladus. For robotic missions to operate in the outer solar system at a production level comparable to that of the Mars rovers, they will require greater autonomy, not only in mapping and navigation, but also in experimental design and sensor placement.

I will introduce our initial efforts to develop a software-based inquiry engine that relies on a generalized form of information theory called the inquiry calculus. This computational technology enables one to compute the optimal experimental question to ask in a given situation. This technology depends on predicting the probable answers to questions, and selecting the question based on the entropy of the probability distribution of potential answers. I will demonstrate these concepts on a robotic arm that has been programmed to identify and characterize shapes on a playing field using only a simple light sensor.

Dr. Kevin Knuth recently presented his work on Intelligent Autonomous Machines at the 9th Annual International Society for Bayesian Analysis (ISBA 2008) on Hamilton Island, Queensland, Australia, from 21-25 July 2008.  The presentation included a demonstration of our prototype intelligent robotic arm.

The abstract can be downloaded here.

This month’s issue of IEEE Spectrum Online has an interesting article by Rodney Brooks on the future of artificial intelligence titled “I, Rodney Brooks, Am a Robot“.

Kevin Knuth

Parallax has developed a “Memory Stick Datalogger“.  For $35, this little board takes 5V power and hosts a USB Type A (female) jack on one end and a row of pins providing both SPI and UART interfaces at the other end.  The idea is that you plug in a USB mass storage device, for instance a USB Flash drive, containing a FAT filesystem.  A microcontroller that speaks UART or SPI can then edit files on the USB drive using a DOS-like language.

This lets you write to cheap storage — $8 for a 1GB USB Flash stick these days — and access those same files from Windows or Linux from the filesystem level.  Cheaper devices, for instance Futurlec’s SD/MMC Mini Board ($7), let you read and write Flash memory in SD card form, but they require you to (a) speak the SD card language and (b) implement the FAT filesystem access yourself.  (Note: C libraries are available for both of these purposes.)

Since the USB mass storage language is standardized, you could probably connect a USB hard disk enclosure to the Memory Stick Datalogger to gain access to very large data storage areas.  The product manual is not clear on this point, however, and I haven’t had a chance to test compatibility with hard disks.