(Credit:
MIT)
Micro Air Vehicles (MAVs) may be small, but they're costly, so researchers have devised ways for them to fly in GPS-denied urban and indoor environments where they could otherwise get lost or crash.
Existing highly-precise, non-GPS navigation units are too large, heavy, and expensive to install on an MAV. But the Robust Robotics Group at MIT's Computer Science and Artificial Intelligence Laboratory addressed this problem by developing algorithms that allow a miniature robo-quadrocopter to estimate their relative position, identify a clear path and then fly through dense air space.
"The size, weight, and budget limitations of micro air vehicles (MAVs) typically preclude high-precision inertial navigation units that can mitigate the loss of GPS," according to the MIT release. "We are developing estimation and planning algorithms that allow MAVs to use environmental sensors such as range finders to estimate their position, build maps of the environment, and fly safely and robustly."
The laser range-finder estimates the MAV's position, yaw angle, and altitude information from surrounding landscape out to about a 12 foot range.
In recent tests, the MAV navigated cluttered offices and unknown hallways and found its way through other unmapped environments by using its onboard laser scanners and cameras to build its own map, according to MIT.
MIT's secret sauce is based on the Belief Roadmap (BRM) algorithm, which performs searches in the MAV's "information space" to determine the "minimum expected cost path for the vehicle," according to a learned paper on the subject. Anything that mentions the Unscented Kalman Filter is worth a click.(PDF)
(Credit:
DARPA)
What if the wisdom of Web could be yours, without having to read through it one page at a time? That's what the military wants.
DARPA has hired a company to develop a reading machine to reduce the gap between the ever increasing mountain of digitized text and the intelligence community's insatiable appetite for data input.
BBN Technologies was awarded the $29.7 million contract to develop a universal text engine capable of capturing knowledge from written matter and rendering it into a format that artificial intelligence systems (AI) and human analysts can work with. (PDF)
The military will use the Machine Reading Program, as it's officially called, to automatically monitor the technological and political activities of nation states and transnational organizations-which could mean everything from al-Qaeda to the U.N.
To pull it off, BBN will "develop techniques that can generalize across the linguistic structure and content of diverse documents to extract relations and axioms directly from text rather than relying on a knowledge engineer to encode such information."
"The machine reading system that DARPA envisions is not evolutionary, but revolutionary," said BBN Technologies VP Prem Natarajan. "Such a system could eliminate many of the impediments to stability that our military faces such as a lack of understanding of local customs, and give us the ability to assess global technology developments continuously."
However, BBN also expects the program to enable a plethora of new civilian applications, everything from intelligent bots to personal tutors. The system could provide unprecedented access and automated analysis of the world's libraries, allowing for vastly expanded cultural awareness and historical research, according to the Cambridge, Mass.-based company.
BBN already offers a broadcast monitoring system that automatically transcribes real-time audio stream and translates it into English, creating a continuously updated, searchable archive of international television broadcasts.
"Imagine if the Reading System could be applied to scouring the World Wide Web for good deals on cars one time, and then applied to integrating new findings in genetics to an automated theory of disease," DARPA posits in its bid solicitation.
It should also be able to crank out one a heck of a term paper.
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