Download Honda Using Experimental New ASIMO for Disaster Response

Honda Using Experimental New ASIMO
for Disaster Response Research
By Evan Ackerman and Erico Guizzo
Honda's experimental disaster-response robot is learning to climb a vertical ladder.
During the Fukushima crisis in Japan, the lack of Japanese robots that were
available to help out was notable. There was some question as to why
Honda didn’t just send ASIMO (arguably one of the most sophisticated and
capable humanoid robots in existence) to help out. The simple answer is
that ASIMO wouldn’t be able to handle that kind (or any kind) of extreme
environment. The robot was never intended to be a disaster mitigation
robot; it was designed to work in offices, specifically the kind of offices that
have notexperienced an earthquake, explosion, alien invasion, sharknado,
or other messy event. Honda is clearly aware of ASIMO’s limitations in
tackling these kinds of situations, and that’s probably why (as we reported
two years ago) the company has been developing a new version of ASIMO
that is specifically designed for disasters.
At the IEEE/RSJ International Conference on Intelligent Robots and
Systems (IROS) this week, Honda engineers presented a pair of papers on
research they’re doing with disaster-response humanoid robots. The
researchers report that they’ve been focused on complex tasks such as gait
transitions and ladder climbing. It was nice seeing that their ASIMO-based
experimental humanoid is already doing some very impressive things.
“When will they give me a name?”
The two papers that Honda presented at IROS weren’t actually about this
new robot at all: the first was on “Dynamic Gait Transition Between Bipedal
and Quadrupedal Locomotion,” and the second was “Robust Vertical
Ladder Climbing and Transitioning Between Ladder and Catwalk for
Humanoid Robots.”
It’s clear that the company is still working on this new platform and isn’t
ready to officially introduce it to the world. The robot [pictured right]
doesn’t even have a name. Honda refers to it as “experimental humanoid
robot.”
Here are some specs from the papers, compared to the specs of ASIMO:
It looks like there are some sensors in the head that we can’t quite make out,
but most notably, it doesn’t appear to be tethered for power, and that giant
white box is either batteries, some kind of fuel cell, a miniature fusion
reactor, or a gerbil on a wheel. It’s evident that the new robot is very
different from ASIMO, although we have to assume that there’s a significant
amount of ASIMO DNA that would go into any new humanoid robot from
Honda. And for the record, we did ask the researchers to tell us more about
everything (or anything, really), but they referred us to Honda PR, which
means that nobody is going to tell us anything.
Now let’s take a look at the research that the Honda engineers presented,
which provides a few clues about what the company might be planning for
its robot.
The robot can go from a catwalk onto a vertical ladder . . .
. . . and then it is able to ascend fairly briskly.
In the DARPA Robotics Challenge Trials, robots had to climb a very steep
set of stairs. That was pretty hard, and in the DRC Finals, the stairs were
shorter and not steep at all. Honda has no time for stairs, and has their
robot climbing a vertical ladder, including transitioning onto it and off of it
from a narrow catwalk. We’ve never seen a robot demonstrate this behavior
before. It’s difficult to do because ladders are slippery, and small slips,
rotations, or other positional errors and motions that vary from planned
trajectories can result in a fall.
The control method that Honda has developed makes continuous real-time
estimates of the posture of the robot and adjusts subsequent contact
positions to compensate for any errors, resulting in “robust multiple rung
vertical ladder climbing and bidirectional transitioning from a ladder to a
catwalk.” Apparently the robot is able to ascend fairly briskly, and Honda
said it is working on even faster and more efficient ladder climbing gaits,
including “trotting” and “pacing.” I assume these are terms for climbing
gaits that use fewer than two steps per rung.
The robot can quickly transition from biped to quadruped and back.
The DRC also highlighted the advantage of multimodal locomotion: robots
that weren’t restricted to walking, but could also drive on wheels or switch
to a quadrupedal mode whenever it was necessary or advantageous to do so.
Honda is also exploring this idea, except they’re trying to do it without any
compromising of their humanoid form. Essentially, they’re making a robotic
ape.
Unlike other humanoid robots that can transition to quadrupeds, Honda’s
robot can do so dynamically, without maintaining a static center of gravity.
This makes it very quick, able to autonomously go from standing to all fours
in about 2 seconds. To do that, it relies on neat trick: it spins a pair of
flywheels in the torso. How cool is that? It can get back up again just as
quickly, and move continuously at about 0.5 km/h the entire time. The
balancing software is an extension of the algorithms that keep ASIMO
upright, and the researchers hope to develop autonomous planning
software that will allow the robot to locomote dynamically through arbitrary
environments.
Concept art showing what Honda envisions for its disaster response robot.
From the current state of this research, we wouldn’t be surprised if Honda
had started in on this project almost immediately after Fukushima. They’re
irritatingly good at keeping secrets over there, so we’re feeling pretty lucky
that we even got to see this much. Hopefully, we’ll be getting sporadic
updates from now on, since it seems like Honda has decided to let its
researchers present at conferences. We’re not at all sure what the endpoint
is, or when we might see a robot that could be called complete, but it’s
fantastic that Honda is actively working on disaster robotics, and we’re very
much looking forward to learning more. Eventually.
“Robust Vertical Ladder Climbing and Transitioning Between Ladder and Catwalk for
Humanoid Robots,” by Masao Kanazawa, Shunichi Nozawa, Yohei Kakiuchi, Yoshiki
Kanemoto, Mitsuhide Kuroda, Kei Okada, Masayuki Inaba, and Takahide Yoshiike, and
“Dynamic Gait Transition Between Bipedal and Quadrupedal Locomotion,” by Takumi
Kamioka, Tomoki Watabe, Masao Kanazawa, Hiroyuki Kaneko and Takahide Yoshiike,
from Honda R&D, were presented this week at IROS 2015 in Hamburg, Germany.
First ‘What is Quantum Computing?’
A classical computer has a memory made up of bits, where each bit represents either a one or a
zero. A quantum computer maintains a sequence of qubits. A single qubit can represent a one, a
zero, or anyquantum superposition of those two qubit states; a pair of qubits can be in any
quantum superposition of 4 states, and three qubits in any superposition of 8 states. In general, a
quantum computer with
qubits can be in an arbitrary superposition of up to
different states
simultaneously (this compares to a normal computer that can only be in one of these
states at
any one time). A quantum computer operates by setting the qubits in a controlled initial state that
represents the problem at hand and by manipulating those qubits with a fixed sequence
of quantum logic gates. The sequence of gates to be applied is called a quantum algorithm. The
calculation ends with a measurement, collapsing the system of qubits into one of the
states, where each qubit is zero or one. The outcome can therefore be at most
pure
classical bits of
information. Quantum algorithms are often non-deterministic, in that they provide the correct
solution only with a certain known probability.
An example of an implementation of qubits for a quantum computer could start with the use of
particles with two spin states: "down" and "up" (typically written
and
, or
and
). But
in fact any system possessing an observable quantity A, which is conserved under time evolution
such that A has at least two discrete and sufficiently spaced consecutive eigenvalues, is a
suitable candidate for implementing a qubit. This is true because any such system can be
mapped onto an effective spin-1/2 system.
How Much Power Will Quantum Computing Need?
By Jeremy Hsu
Posted 5 Oct 2015 | 14:22 GMT
Photo: D-Wave Systems
Google’s Quantum AI Lab has installed the latest generation of what DWave Systems describes as the world’s first commercial quantum
computers. Quantum computing could potentially solve certain problems
much faster than today’s classical computers while using comparatively less
power to perform the calculations. Yet the energy efficiency of quantum
computing still remains a mystery.
For now, D-Wave’s machines can scale up the number of quantum bits
(qubits) they use without significantly increasing their power requirements.
That’s because D-Wave’s quantum computing hardware relies on a
specialized design consisting of metal niobium loops that act as
superconductors when chilled to a frigid 15 millikelvin (-273° C). Much of
the D-Wave hardware’s power consumption—slightly less than 25 kilowatts
for the latest machine—goes toward running the refrigeration unit that
keeps the quantum processor cool. The quantum processor itself requires a
comparative pittance.
“The operation of the quantum processor itself requires remarkably little
power—only a tiny fraction of a microwatt—which is essentially negligible in
comparison to the power needs of the refrigerator and servers,” says
Colin Williams, director of business development & strategic partnerships
at D-Wave Systems.
The new 1 000-qubit D-Wave 2X machine installed at Google’s lab has
about double the qubits of its predecessor, the D-Wave Two machine. But
the minimal amount of power used by the quantum processor means that
“the total system power will still remain more or less constant for many
generations to come” even as the quantum processor scales up to thousands
of qubits, Williams says.
D-Wave can currently get away with this because the same “cryostat” unit
that uses so many kilowatts of power would still be sufficient to cool much
larger quantum processors than the ones currently in use.
"It would be similar if you attach a large cooling device to your PC that uses
many kilowatts of power—you would barely see an increase in power
consumption when going to larger systems since the power is dominated by
the large cooling infrastructure," says Matthias Troyer, a computational
physicist at ETH Zurich.
The ability to scale up a D-Wave machine’s computing capabilities without
increasing its power consumption may sound promising. But it actually
doesn’t say much about the power efficiency of quantum computing
compared with classical computing. Today’s D-Wave machines perform
about as well as a high-end PC on certain specific tasks, but they use far
more power based on their extreme cooling requirements. (High-end
computing cores require just tens of watts of power.)
“While the ‘flat power requirement’ is a good statement to make for
marketing, it is unclear at the moment what the true power needs are once
the device is optimized and scaled up,” Troyer says. “Right now they need
orders of magnitude more power than competing classical technology.”
However, it’s not exactly a fair comparison, Troyer says. “On the power side,
they are currently losing,” he says. But the D-Wave machine “is not
engineered to be power saving. It may pay off again at some point.”
Scott Aaronson, a theoretical computer scientist at MIT and a D-Wave
critic, seemed bemused by the idea of D-Wave having a power advantage of
any sort. Referring to D-Wave’s reliance on a crygenic cooler he wrote in an
email: “It’s amusing chutzpah to take such a gigantic difficulty and then
present it as a feature.” He pointed out that D-Wave might need an even
more power-hungry cooling system to create lower temperatures that
improve its quantum processors’ chances of a “speedup” advantage over
classical computing in the future.
D-Wave’s quantum annealing machines represent just one possible
computer architecture for quantum computing. They’re designed to solve a
specialized set of “optimization problems” rather than act as universal logicgate quantum computers. (The latter would be super-fast versions of today’s
classical “gate-model” computers.) Google’s Quantum AI Lab has invested
in both D-Wave’s machines and in exploring development of universal
logic-gate quantum computers.
In the end, Troyer expects power requirements for quantum computing to
probably be “linearly proportional” to the number of qubits and their
couplings, as well as proportional to the number of times operators must
run and recool the system before it finds the solution.
Quantum computing’s big advantages probably won’t begin to emerge until
engineers build machines with many thousands or possibly millions of
qubits. That’s still a ways off even for D-Wave, which has chosen to scale up
the number of qubits in its processors fairly quickly. Most quantum
computing researchers have opted for a much slower approach of building
quantum computing devices with just several qubits or tens of qubits,
because of major challenges in correcting for qubit errors and maintaining
coherence across the system.
Still, both D-Wave and independent quantum computing labs share the
same general goal of building machines that can exploit the “spooky
physics” of quantum physics. Quantum computers could potentially
perform many more calculations at the same time than classical machines.
If quantum computers can beat classical computers in terms of “time to
solution,” they could also prove more power-efficient at the end of the day.
“If a quantum device can solve a problem with much better [time to
solution] scaling than classical computing, it would also win on power,"
Troyer says.