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Courtesy of New Scientist Magazine
AS THE YELLOW PLAYER intercepts the orange ball cannoning off the board that surrounds
the playing field, the blue goalkeeper moves out to cut down the attacker's angle on goal.
But instead of shooting, the forward passes the ball to a team-mate streaking up the left
side of the field, who darts around the sluggish goalkeeper and pops the ball into the
net. Score one for the yellow team from Newton Labs in Seattle, in a crushing 20-0 defeat
of the blue SOTY team from South Korea in last November's final of the first ever
Microrobot Soccer Tournament. In just over a month, the teams will meet once again to try
to knock Newton Labs off the winner's rostrum.
The MIROSOT, as it's known, is the brainchild of Jong-Hwan Kim, his colleagues and
students at the Korea Advanced Institute of Science and Technology (KAIST) in Taejon,
South Korea. They hope football will become a touchstone, stimulating the robot builder's
art in much the same way that chess motivates artificial intelligence research. Robot
football makes heavy demands in all the key areas of robot technology: mechanics, sensors
and intelligence. And it does so in a competitive setting that people around the world can
understand and enjoy. The hope, of course, is that by discovering how to get a robot to
move with agility, see with acuity, and think perceptively in the limited context of a
football game, it will be possible to use the same techniques to build robots to carry out
other, more useful tasks.
Pitched battle
Here the analogy with chess-playing and AI starts to break down, since in several decades
of trying, there's not much evidence that the methods developed to allow computers to play
chess to grandmaster level have any use beyond the edge of a chessboard. But the robot
builders of the MIROSOT believe firmly that their case is different, probably because much
of the challenge of robot football centers on the hardware issues of mechanical motion and
vision processing rather than the pure information-processing problems that characterize
chess programs.
November's tournament brought together 23 teams from nine countries on the grounds of
KAIST, where they competed for the Hanminjok Cup. The same basic rules will apply for the
second tournament, this June. Each team consists of just three robots. And each player's
mechanics and "brain" must be packed into a cube no larger than 7.5 centimeters
on a side. Unlike a real football pitch, the 130-centimeter by 90-centimeter playing field
is bounded on all sides like an ice-hockey rink to prevent the ball-an orange-painted golf
ball-from going out of play.
The teams gather information about the location of the ball and players from TV cameras
suspended above the pitch. That information goes first to an off-pitch controller and then
by radio to the robots themselves. And here is where the first big difference appeared
between the teams-they vested differing degrees of autonomy in the robots themselves. All
but two groups of researchers transmitted just positional information to their robots,
allowing the machines to find their own way to the ball. These robots carried on-board
sensors to help them avoid collisions with other machines.
Brainless
One of the two exceptions was the Newton Labs team, which went for a more centralized
approach. Its robots were "brainless", and the offpitch controller dictated
their behavior totally, telling them where to move and at what speed. These robots had no
collision-avoidance sensors. So the competition did not simply set like against like:
there was a "generational conflict" at work as well, between the old-style
centrally planned strategies, and the beginnings of the more ambitious strategy of
allowing robots to make their own decisions.
My own involvement with the MIROSOT stemmed from a chance encounter early last year in
Japan with Kim at a meeting on artificial life and robotics. I had just given a talk on
some football simulations that I'd carried out on Super Bowl XXIX, the championship event
that capped the 1994-95 season in the American National Football League. These experiments
consisted of playing the game between the San Francisco 49ers and the San Diego Chargers
100 times in my computer, using a program that rates all the players in the NFL by their
individual playing characteristics. My goal was to see if the odds quoted by the Las Vegas
bookmakers for the game bore any resemblance to statistical reality as calculated by my
computer*.
For me, the interesting theoretical point of this experiment is that football is a classic
example of what is termed a complex, adaptive system. These are systems composed of a
medium-sized number (up to a few hundred thousand) of "agents" that are
intelligent and adaptive. This means they take actions based on rules, and are adaptive in
that they can change the rules or invent new ones if they see that the old ones are not
working. Furthermore, the agents must make choices on the basis of incomplete information
about what others in the system are doing. Other good examples of such systems are
financial markets, immune systems and road-traffic networks, in which the agents are
traders, molecules and drivers respectively.
A number of researchers have studied the behavior of these systems, mostly in the virtual
reality of computer memory. Robot designers have a unique opportunity to go a step further
and build physical agents capable of interacting and adapting. Indeed, creating groups of
cooperating automatons is a new and growing area of research in robotics. During my
presentation in Japan I said there was no better test problem for a robot builder's
tentative theory of a working complex, adaptive system than a football game.
It was after this that Kim told me about the MIROSOT. My first reaction was to bemoan the
fact that I didn't build robots. "No problem," he replied. "You can come
and be one of the referees and make sure none of those damned robots cheat." How
could I refuse? So in early November, I packed my striped shirt, a set of red and yellow
cards, and a whistle, and an electromagnetic zapper for frying the brains of any cheating
robot, and headed for Taejon.
Piggybacked on the sporting competition was a symposium replete with technical discussions
of the approaches employed by competing teams to get their robots to play a decent game of
soccer. These problems centered on three main areas. First, there are the purely
mechanical problems, such as how to move the robots about the field and get them to change
direction quickly as the ball rolls around. On top of that come the "sensory"
problems concerned primarily with seeing the ball and the other players. And finally there
are strategic problems associated with processing information about the game and designing
sensible strategies and tactics to win.
At this early stage in the development of microrobot football, researchers have yet to
work out the best answers to these problems. This in itself leads to another difficulty:
how should the teams combine their suboptimal solutions to each problem in order to
produce the best overall result? And all this within the confines of a 7.5-centimeter
cube. Newton Labs' centralized approach used a very sophisticated visual system and a
rather primitive playing strategy. So the Seattle researchers chose to devote most of the
space in their robots to mechanical motion. Others, such as the SOTY team from KAIST,
tried to compensate for inferior visual systems by implementing more elaborate playing
strategies, through algorithms telling their players how to react in different situations.
These bigger brains, however, forced the KAIST team to compromise on physical attributes
such as speed.
One difficulty confronting all the teams was what one might term the "poverty of
power problem". The power needed to operate the robot's mechanics is considerable,
and each robot has to carry its own power source. Existing battery technology being what
it is, this limited the length of each half of a MIROSOT game to five minutes.
These technological limitations make refereeing a robot soccer game an experience in both
humor and frustration. The robots' vision systems are often swamped by information and
liable to be confused by certain colors, leading to players pushing the ball into their
own goal. At other times, goalkeepers stand as motionless as the Sphinx while the ball
slowly rolls past them into the net. And if the referee were to follow the rules to the
letter, the number of free kicks for off-side and penalties for fouling an opponent by
running into them would slow play to a glacial crawl. A certain flexibility in
interpreting the rules is needed to keep things moving.
So what kind of solutions to the technical problems separated the winners from the losers?
The answer is as simple to state as it is difficult to implement: emphasize speed and
vision at the expense of brainpower. How appropriate! Here is one place where robot soccer
makes contact with its real-life counterpart. It was clear from the demo game that opened
the tournament that the Newton Labs robots, with their superior vision and speed, would
run off with the cup. In their five games, the Newton robots won 12-3, 13-0, 15-1, 19-0
and 20-0. By comparison, no other team scored more than eight goals in any game.
Laughable state
On the face of it, the Newton Labs victory does little to push forward the development of
autonomous agents, which is one of the underlying ambitions of the MIROSOT organizers. The
Seattle robots relied on a single brain that had "complete" information about
the state of play. By comparison, most losing teams opted to let their robots play some
part in decision-making based on "local" information. And no robot in the
competition appeared to be able to adapt its tactics on the basis of what it had learnt
during a game. So while the teams may have been complex, they cannot yet be called
complex, adaptive systems.
For the present, then, robot football appears to be in the laughable state that computer
chess was in during the 1950s. But no one is laughing at chess-playing programs today.
Whether a similar scenario will unfold with computer football is debatable. No one expects
robots ever to take the field against human footballers. But at least the skills shown by
the teams participating in MIROSOT showed great potential for much more refined play.
During a discussion at the MIROSOT, the idea was raised that it might be interesting to
introduce a new class of play, in which human opponents control one of the competing robot
teams by using, say, a joystick, Nintendo-style. This would introduce a component of
human-machine competition that would add spice to the tournament and further motivate the
robot builders. In any case, everyone at the MIROSOT went home enthused about the whole
idea of robot football, vowing not to let the Newton Labs team win in June. A new life
form-the microrobot footballer-has been created. The next MIROSOT should give us a better
indications about the evolutionary pathway this creature will follow.
Maradona, eat your heart out
BUILDING A MACHINE with world-beating football skills into a 7.5-centimeter cube takes a
good deal of ingenuity. And the team from Newton Labs in Seattle proved to be masters of
improvisation. The two Canon motors that drive each robot should probably have been
whirring inside someone's photocopier. Salvaged from a surplus store, they were too big to
sit opposite one another without breaking the size constraints. So they had to be offset,
and connected to the wheels by a drive chain the team concocted from bits of Lego.
With wheels mounted on the sides, each robot needed casters front and back to stop it
tipping. But the team-Anne Wright, Randy Sargent, Carl Witty and Bill Bailey-could not
find wheels small enough. They settled instead for beating bits of drinks cans into
sliders. Finding a small radio receiver also proved a problem until Sargent found a pair
of wireless headphones in the local branch of Radio Shack. The receiver electronics fitted
neatly on each robot, while the transmitter was connected to the off-pitch controller.
No corners were cut, however, with the vision system, which tracks colored blobs in
successive video frames and can identify their shapes. During the matches, a video camera
viewed the pitch from above. To this the team linked its vision system, which told the
master controller the whereabouts of the orange ball, together with the position and
orientation of the Newton robots-which had yellow rectangles on their lids-60 times a
second. The team's nearest rival could refresh its gaze only 10 times a second.
This system was a key to the team's success. The controller continually predicted the
position of the ball and ran iterative calculations to decide the best tactics for the two
forwards. It calculated where the ball would be in, say, a second's time and then asked
whether either robot could reach that position and score a goal. If the answer was no, it
moved on to calculate the position two seconds ahead, and so on. "We would run
several hundred of these simulations 60 times a second," says Sargent.
Eventually, the controller would radio to one of the forwards, telling it how fast to run
its motors in order to hit the ball into the net directly, or off the side board. "We
bother about the angle at which we hit the ball, but don't care too much about the
velocity other than it should be moving as fast as possible," says Wright. "We
like to keep the ball moving quickly so that nobody else can deal with it."
Although the Newton robots had fast reactions, their aim was not always true. Their jerky
movements introduced errors that sometimes sent the ball rebounding off the backboard. Yet
on occasion, even this looked deliberate. "If you look at footage of the games, you'd
swear they were passing. But it wasn't intended," says Sargent. It emerged simply
because 1/60th of a second after the first forward shot at goal, the controller was
planning an intercept course for its team-mate.
The Newton robots had only a few other rules. A forward not playing the ball was ordered
to retreat between the ball and its own goal. The forwards were also subject to two
programs that acted as "repelling forces". One strong, short-range force kept
them away from other robots and the sides, while a weak, long-range force kept each
forward as far from its partner as possible.
The third robot, the goalkeeper, was directed by a simple program that kept it moving from
side to side, in line with the ball. The only change to this was if the controller
calculated that the ball would go near the goal, in which case the keeper moved sideways
to intercept it. "Other teams had more complex strategies," says Sargent.
"Some would move forward and back and go to meet the ball. They didn't seem to be so
effective."
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