Research Horizons Magazine
Around him stand a gaggle of robots, some with trash can figures, others
resembling miniature all-terrain vehicles. They appear to be merely functional,
plodding pieces of equipment. But these unlikely contraptions can "think"
in the sense that they can react to and reason about their environment.
Collins, a senior research engineer in the Georgia
Tech Research Institute's Electronic Systems Laboratory, likens the
"minds" of these machines to those of clever insects that have
learned to thrive. "A cockroach is intelligent because it can survive
and do the things it needs to do well. By that definition, these robots
are smart," he says.
In the Mobile Robot
Laboratory, Collins collaborates with researchers in the College
of Computing to create machines that can make complex decisions. They
are exploring two new applications in a study funded by the Defense
Advanced Research Projects Agency (DARPA). Researchers are teaching
the robots how to search through rooms for biological hazards, and perhaps
to find, intercept and destroy a moving enemy tank on the battlefield.
The robots perform the tasks on their own. No one uses a joystick to guide
Some university robot labs focus on low-level performance, such as movement
guidance systems. Others work to achieve higher-level reasoning in machines.
But researchers in Georgia Tech's robot program are pioneering efforts
to integrate those separate levels of functioning to design behavior-based
robotics for both military and private-sector applications.
"Our goal is to create intelligence by combining reflexive behaviors
with cognitive functioning," explains Ronald
Arkin, a Regents' professor of computer science and director of the
lab. "This involves the issue of understanding intelligence itself.
Is it complex? Or just an illusion of complexity?"
The task of building knowledge and awareness for machines is huge. Consider the different kinds of behavior humans use when driving their cars. People can motor along without being conscious of actively driving (reflexive behavior), but that changes if they get lost. Then they think about how to navigate (cognitive reasoning).
"We are figuring out how to make robot architecture both act and
'think,' using learned and acquired skills," adds Arkin, who specializes
in development of high-level, behavior-based robotic software. He builds
it using abstract behaviors that capture both sensing and acting, but
can be reasoned as separate pieces of intelligence. Arkin's approach is
influenced by psychology and neuroscience.
Collins maps such software into hardware. He also works with sensors (both hardware and software) to develop methods of acquiring and processing perceptual data for robots in real time, using global positioning system (GPS) data and other information.
To help robots learn, the researchers use a variety of techniques. "Learning
momentum," a technique pioneered by Arkin and his research team,
involves teaching a robot that if a behavior is working well, it should
continue doing it. The robot adapts its behavior in response to the environment
and its own performance. Another technique called reinforcement learning
uses computer-generated "rewards" to tell the robot it has made
good decisions - and should continue doing so.
The researchers are also investigating the best way for humans to interact
with computers. "I am keenly interested in understanding psychology
between humans and robots," Arkin says.
In related work, Collins is collaborating with Assistant Professors Tucker Balch and Frank Dellaert and research scientist Daniel Walker, all from the College of Computing. The researchers are developing a colony of 100 small robots to simulate a large-scale system that may include humans, robots and other machines. Researchers want the colony to collaborate in unfamiliar and rapidly changing environments - where sensor readings are subject to errors - to gather information quickly from many vantage points.
They plan to outfit the colony's robots with simple, inexpensive sensors
that can recognize the positions and movements of others in the group.
This capability provides an indirect means of communication and cooperation
similar to that found in colonial insects, such as bees, which can direct
each other to food sources, Collins explains. By making many, simultaneous
measurements and communicating the values between robots, the colony will
be able to combine a large amount of imprecise information to produce
a more accurate map of the entire region the colony occupies.
Collins recognizes the challenges that researchers face, but remains hopeful about advances in the technology.
"It is inevitable that our machines will become smarter at anticipating
our needs and performing their functions without frequent human intervention,"
he predicts. Sophisticated robots "are still a long way off, not
just because of the intelligence issues, but also because of problems
with power storage, locomotion capabilities, perception and other limitations.
But basic androids will probably happen eventually -- quite possibly within
the lifetimes of today's children."
RESEARCH NEWS & PUBLICATIONS OFFICE
Georgia Institute of Technology
75 Fifth Street, N.W., Suite 100
Atlanta, Georgia 30308 USA
Tom Collins, Electronic Systems Laboratory, Georgia Tech Research Institute (404-894-2509); E-mail: (firstname.lastname@example.org) or Ronald Arkin, College of Computing (404-894-8209); E-mail: (email@example.com)
WRITER: Renee Twombly