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Runbot - robots that learn to
walk, run better with time
Self learning runbots learn how to
walk and run better by themselves and
improve.
15 July, 2007
Walking robots, so far only seen in
science-fiction movies, could become a
reality with engineers building a
biped machine that adjusts its gait to
climb slopes without falling over.
The highly sophisticated robot – named
‘RunBot’ – developed by engineers at
the University of Gottingen in
Germany, learns to walk like a human
toddler.
On its first two or three attempts at
climbing a ramp, the machine,
consisting of a pair of legs and a
trunk, loses its balance and topples
backwards, but it quickly learns to
correct itself and stay upright by
taking shorter steps and leaning
forwards. On reaching another flat
surface, the robot adjusts its gait
again.
Robots that walk upright in this way
present a good deal of great technical
challenges, but such abilities will be
essential if bipedal domestic robots
that can help around the house, carry
shopping, or care for the elderly are
to become a reality.
RunBot already holds the record for
robot speedwalking and it can bowl
along at more than three leg-lengths
per second, slightly slower than the
fastest walking human.
The German team of engineers upgraded
the machine by giving it an infrared
eye and an “accelerometer sensor”
which acts like the balance mechanism
in the human inner ear.
Both the infrared eye and
accelerometer sensor are linked to an
artificial ‘brain’ or neural network
which decides how the robot should
respond when it spots a slope ahead
and feels its balance slipping.
The basic walking steps of RunBot are
controlled by reflex information
received by peripheral sensors on the
joints and feet of the robot, as well
as the accelerometer which monitors
the pitch of the machine.
These sensors pass data on to local
neural loops – the equivalent of local
circuits – which analyse the
information and make adjustments to
the gait of the robot in real time.
Information from sensors is constantly
created by the interaction of the
robot with the terrain so that RunBot
can adjust its step if there is a
change in the environment.
As the robot takes each step, control
circuits ensure that the joints are
not overstretched and that the next
step begins.
But, if the robot encounters an
obstacle, or a dramatic change in the
terrain, such as a slope, then the
higher level functions of the robot –
the learning circuitries – are used.
Of the robot’s total weight, 70% is
concentrated in its trunk. RunBot run
up slopes without falling by
shortening its stride and leaning
forward by just the right amount.
Since the ‘brain’ learns from
experience, the robot’s performance
improves over time.
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