Brainless wondersNew Scientist
18 July 1988
By Kurt Kleiner
shelves of Mark Tilden's lab are lined with hundreds of robots—robots
that walk, robots that roll, robots that crawl suicidally through
minefields, even robots designed to float in space. Most are small
enough to sit on the palm of your hand, and seem almost toy-like. The
impression is reinforced by the green rubber dinosaur and the model of
the Star Wars robot R2-D2 which share shelf space with them.
inside these tiny machines something intriguing is going on. Using
simple networks of a few transistors, resistors and capacitors, and
avoiding conventional computer processors entirely, Tilden has been
able to coax complex, adaptive behaviours out of his robots. They are
This approach is at odds with mainstream
robotics, which has grown up with digital technology. Whether it's a
new, custom-built industrial robot or the latest automaton to display
artificial intelligence (AI), most cutting-edge machines rely on
Tilden, who works at the Los Alamos National
Laboratory in New Mexico, believes this approach is doomed to failure.
He calls it the Asimovian approach, after the science-fiction writer
Isaac Asimov, who inspired the first generation of modern robot
designers. It's based on the idea "I'm a rational being, therefore I
should be able to design another rational being," he says. The trouble
is that you have to increase processing power exponentially in order to
achieve a linear increase in ability. "To make a robot that makes you
toast costs $20 000. To get that same robot to butter your toast costs
an additional $300 000."
He speaks from experience. Early on he
tried to design a processor-based, jack-of-all-trades house-cleaning
robot. In the end the complexities of programming the machine got the
better of him. "Now I use it as a hat rack," he says. So Tilden has
gone to the other extreme. His approach is to build cheap, simple
robots that are competent at a single task. If you want another task
performed, you design another simple robot.
In his home he has
dozens of robots to do the cleaning. Some of them are floor
cleaners—they constantly skitter around, sweeping the floors and
delivering the dust to a central depot. Each can clean only a little
bit, but since there are several of them, and all they do all day is
clean floors, the floors stay immaculate. Others do nothing but glide
up and down his windows, cleaning as they go. "It's a balanced robot
environment," he says. "It's a robot ecology."
A matter of timingAll
this and not a microprocessor in sight. So how do these creatures work?
At the heart of them all is what Tilden calls a nervous net—for which
he holds the patent. The net is essentially a ring of artificial
neurons made up of pulse delay circuits. Each circuit consists of a
resistor, a capacitor and an inverter, and stores up charge until it
reaches a certain threshold. Then it fires. By hooking up the output of
one neuron to the input of the next, Tilden can send a timed pulse
round the ring that pauses at each neuron in turn before moving on to
The central controller for, say, a four-legged robot,
would take the shape of a ring of four neurons, one for each leg. Each
neuron would in turn connect to a further four "leg neurons" that
command two motors—one to move the leg up and down, the other to manage
motion forwards and backwards. A pulse passes round the controller, but
as each neuron fires it also causes the leg neurons to fire, moving
each leg in turn. For this "creature", walking is not a carefully
programmed task, but something that simply emerges from the interplay
of the neurons.
Another clever aspect of the nervous net is
that, so long as the motors take their power from the same source as
the control pulse, a simple form of feedback is built into it. When a
leg is slowed by an obstacle, the motor draws more power, leaving less
for pulse generation. This automatically slows down the walking
sequence until the leg is free to move again.
more complex applications, sensors can be added to enhance this
feedback effect. By injecting their own pulses into the ring, these
sensors cause the central control neurons to fire with different
timings, modifying how the robot moves. By properly tuning the timings,
a pulse from a sensor which indicates that the robot has hit an
obstacle might make the legs move so they turn the robot left or right
to avoid the obstacle.
As their nervous nets become more
complex, the robots' behaviour becomes harder to predict. Tilden
designs the nets with particular behaviours in mind. But then he has to
tinker with the configuration, finding out through trial and error
which behaviours are produced by which adjustments.
demonstrate his machines, Tilden puts a dozen in a big, shallow box and
carries them outside to a loading bay. The robots are all solar powered
(most have solar cells scavenged from old pocket calculators), and
under the bright New Mexico sun they perk up. They all have wheels, and
their mission is to keep moving. To do this, they head towards light
sources and negotiate obstacles. Each is surrounded by sensors—wires
that form what look like all-round bumpers—which tell the robot when it
has hit an obstacle.
When the obstacle is the side of the box,
the robots just keep turning until they're clear. But when the obstacle
is another moving robot, getting clear can be more difficult. It's in
these robot scrums that different "personalities" become apparent from
different nervous net configurations. Some robots avoid fights and move
away quickly. Others are more aggressive. They ram other robots,
repeatedly triggering their victims' sensors and flooding them with a
fast and erratic flow of pulses. Eventually, the victims' systems
overload and freeze up until a coherent series of pulses starts to flow
One robot is so aggressive it is self-destructive. It
moves quickly, banging repeatedly into any other robot it comes across.
But it always ends up overloading itself and stops in confusion. Tilden
likens it to a guy in a bar who doesn't know when to stop picking
But the nervous net approach is not limited to playing
solar bumper cars. Tilden and his colleagues have proposed launching
hundreds of tiny 14-gram robot satellites into space and using them to
measure the magnetosphere, or equipping each with a small imager and
then combining images from the entire swarm to make a single
high-resolution picture (New Scientist, This Week, 23 March 1996). To
keep themselves oriented correctly, these "satbots" would use
electromagnets connected to a light detector via a simple nervous net.
The light detector would point at the Sun, and if it wandered from this
position the robot would power up the electromagnets to realign it by
pushing off the Earth's magnetic field.
In the lab, Tilden
demonstrates a prototype that consists of three arms arranged like a
camera tripod. At the end of each arm is a coil of copper wire that
serves as an electromagnet. Tilden balances the robot on a stand and
brings a lamp closer. The satellite rocks as it tries to orient itself
towards the light. Gravity defeats it, but in space it would have no
In a more down-to-Earth application, Tilden has taken
some of his walking robots to the Yuma Proving Grounds in Arizona, to
see if they could find and dispose of landmines and unexploded
ordnance. He reasoned that his machines have a number of advantages for
the work. For a start, they can travel across rough terrain more easily
than wheeled devices. The simplicity and robustness of their circuitry
also means his robots could work in conditions of heat, cold, mud or
dust that would defeat more complicated machines. And they are more
likely to survive an explosion. Even if two legs have been blown off,
his robots can still operate, dragging themselves to the next mine.
Even if they are flipped over, they can still crawl along upside down
on their "knees".
Robots don't have to be geniuses to clear
mines. One plan is to use numerous cheap machines that would simply
wander at random, stepping on mines and exploding them. Or they could
be fitted with sensors to detect the mines. They would then either mark
them for later retrieval, pick them up and carry them to a central
site, or simply blow them up.
Tilden says he ran into one
unexpected problem. The soldiers who witnessed the exercise, seeing a
crippled robot continue to drag itself suicidally along looking for
more mines, felt sorry for the machine. This is one of the most
fascinating things about Tilden's machines. His only design criterion
is that they are competent at their given task, yet in carrying out
that task they behave in such complex ways that observers ascribe
personalities to them—even intelligence. But is that justified? "At
what point will competence turn into intelligence? I don't really
care," Tilden says. "Too many people are working on intelligence out
Beyond the best brainsThe notion that
intelligence could arise from such simple machines is not as crazy as
it may seem. It has been championed throughout the 1990s by one of the
gurus of robotics, Rodney Brooks of the Massachusetts Institute of
Technology. He rejected the idea of a central brain, preferring instead
to distribute control to simple components. He showed how complex
behaviours arise from the interaction of those components. In his
six-legged robot, for example, each leg is controlled independently and
walking emerges by timing the actions of the legs. Brooks argues that
intelligence also emerges from the way things—people and robots—
interact with the world.
Tilden admits to being heavily
influenced by Brooks. But Brooks relies on digital logic and
microprocessors, and this is where Tilden parts company with him. "When
something gets beyond a certain degree of complexity, no mind on the
planet, no amount of work, will get around it," he says.
analysis of the problems of microprocessor-based robotics is overly
pessimistic, says Illah Nourbakhsh, an AI specialist and roboticist at
Carnegie Mellon University in Pittsburgh. Take Tilden's assertion that
processor-based robots need exponentially more computing power to
achieve linear increases in ability. This is true in theory, says
Nourbakhsh. But in practice robot designers are getting better at
figuring out algorithmic shortcuts, allowing the robots to make
decisions without having to work through near-infinite decision trees.
And advances in computing are also making a big impact, he says. "It's
definitely the case that many of us in the robotics field do better and
better as computers get better."
Robot rescueUp to now,
it is mostly processor-based robots that have found practical uses.
Researchers at Carnegie Mellon, for example, sent a processor-based
walking robot, Dante, into an active volcano in Alaska in 1994. On the
other hand, as Tilden points out, Dante eventually slipped and fell,
and had to be rescued by helicopter.
Relying too much on
computers has led to undesirable consequences, says Tilden. Many robots
are not truly autonomous but are "puppets"—mechanical bodies tethered
by a data bus to a powerful workstation. Others exist only as
simulations within computers. "Do you know what it's like to go to a
robot conference and not see one robot?" says Tilden. The real
challenge, he argues, is to make robots that can deal with the chaos of
the everyday world. "The inside of a computer is a perfect world," he
says. "The real world is fractal. It's complex. It's dusty."
1989, in a bid to get more people building real robots, Tilden founded
the BEAM Robot Games (BEAM stands for Biology, Electronics, Aesthetics
and Mechanics). In games held all over the world, contestants come
together to see whose robot can walk, jump, swim or fly the best.
Tilden hopes that as more people try out their own approaches, the
robots will evolve into more efficient, more competent machines.
BEAM robots are cheap and relatively easy to make, a large community of
enthusiasts has sprung up. On the Internet dozens of sites offer plans
and tips for building robots out of old calculators and cassette
recorders. One of the best is run by someone who says he's still in
Yet if Tilden's robots are so great, why aren't
they being used for real applications? It's partly a schizophrenic
public attitude to robots in general, says Tilden. People expect a
robot to be a sort of mechanical man, and nervous net robots are far
from that. Some are also afraid of robots—something he calls
"Terminator phobia". When his own mother visits, he has to box up all
of his house-cleaning robots because they make her nervous. "My mom is
convinced my last words are going to be, 'No, no! Back!'"
his robots, there is also one specific limitation. So far, it's been
hard to get high-level functioning out of his robots. While the nervous
nets perform many surprisingly complex behaviours, they're all reflex.
They will never be able to learn, or conduct any sort of planning or
The obvious next step is to add some sort of
brain to these bodies—perhaps a head with a camera for an eye—and let
it guide the action. His analogy is a rider and horse: the rider guides
the horse, but the horse decides where to put its hooves. A
conventional microprocessor could serve as the rider, but you can hear
the distaste in Tilden's voice at the idea. Besides, he says, it's been
tried and hasn't worked well: conventional digital processors don't
mesh well with nervous nets.
Tilden would rather use a neural
network for the rider. His idea is to wire up his artificial neurons in
a complicated array that resembles the mesh of neurons in the human
brain. Like a nervous net, it gives complex performance with relatively
simple circuits. Unlike a nervous net, it is capable of changing over
time—it can learn (see "Cell Wars", New Scientist, 21 February, p 36).
The nervous net would still be there, controlling the body. But the
neural net would do the processing, figuring out which direction to go
and what task it wanted to accomplish.
One of Tilden's first
walking robots used a neural network. But it didn't work. He still has
the machine around, and he fetches it. It starts to walk, but when it
runs into a difficult or confusing circumstance—in this case Tilden
pushing it off balance—it quickly becomes discouraged and, oddly, sits
down on its back end as if sulking. The interaction between neural net
and nervous net is too complicated, and tends to break down easily.
is working on a new design that he thinks will do a better job of
linking the neural and nervous nets. He hopes this will give rise to
much more complex, planned behaviours for his robots.
the summer, he hopes to have a robotic "chess set" that can play
itself. The game won't be played a move at a time, but will be more
like a structured game of bumper cars. The pawns will be simple
nervous-net robots battling enemy pieces for possession of the board's
squares. But the more valuable pieces—queen, bishops and rooks—will be
capable of sensing what is happening several squares away and planning
their moves. The queen will be able to direct pawns to areas where they
are needed and, if she's in trouble, will be able to send a distress
signal to rally her other pieces.
In the long run, Tilden's
ideas may gain ground. But in the short term—unless you build one
yourself—you might have to wait a long time to see a nervous-net robot.
Today, the idea with the best prospects is the satbot, which is being
funded by the US Defense Advanced Research Projects Agency. So it could
be that Tilden's robots will soon be more common in space than they are
on the ground.