Posts Tagged ‘darpa’
BullDog: A Bigger, Scarier Version of BigDog Gets Closer to the Battlefield
Boston Dynamics is building a bigger, sturdier version of the military’s future trusty companion, and will likely unveil it within a few months. The company’s founder and president, Marc Raibert, shared the LS3 robot's progress Tuesday at a keynote speech at the 2011 IEEE International Conference on Intelligent Robots and Systems. Apparently LS3 (Legged Squad Support System) has been nicknamed BullDog, .
Alas, no fun video yet, as Boston Dynamics is apparently waiting for permission from DARPA to release it.
BullDog, like BigDog, is designed to carry hundreds of pounds of gear for armed forces, ambling over rough terrain and following humans without complaint. The larger version will carry 400 pounds, last 24 hours and carry enough fuel for a 20-mile trek. It will also be able to jump over obstacles, and more easily regain its footing after it falls over. BullDog will also have greater navigational autonomy than BigDog, IEEE says.
The most significant change may be that it’s significantly quieter than BigDog, which is quite obnoxiously, buzzingly loud:
Granted, a prancing, unstoppable four-legged metal beast probably doesn’t need stealth to look awesome and surprise the enemy.
BullDog is a 30-month, $32 million project funded by DARPA’s Tactical Technology Office and the U.S. Marine Corps Warfighting Lab. The project started in early 2010, so we anticipate a full unveiling sometime next year.
Until then, content yourselves with some of .
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Scientists Fit Cyborg Beetles With Generators that Turn Their Own Wings into Power Plants
No more battery-driven bugs for DARPA
Now, a team of Michigan researchers may have finally solved the battery problem by demonstrating an energy scavenger that derives power straight from the insects own wing motion. Using a tethered Green June Beetle and a couple of piezoelectric generators mounted on its wings, the researchers were able to generate 45 µW (that’s microwatt, or one one-thousandth of a milliwatt) of power.
What’s more, they think they could improve that by an order of magnitude if they made the beetle a true cyborg and directly implanted the generators to the insect’s flight muscles. That’s enough power to run the onboard neuro-hardware needed to manipulate the beetles--which means basically the ability to tell a Green June beetle to fly depends on the power generated from flight.
That’s pretty cool, considering DARPA and the rest of the cyborg insect research establishment has a variety of roles in mind for the sensor laden drone insects of the future, including search and rescue, intelligence and surveillance, environmental monitoring and the like.
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Scientists Fit Cyborg Beetles With Generators that Turn Their Own Wings into Power Plants
No more battery-driven bugs for DARPA
Now, a team of Michigan researchers may have finally solved the battery problem by demonstrating an energy scavenger that derives power straight from the insects own wing motion. Using a tethered Green June Beetle and a couple of piezoelectric generators mounted on its wings, the researchers were able to generate 45 µW (that’s microwatt, or one one-thousandth of a milliwatt) of power.
What’s more, they think they could improve that by an order of magnitude if they made the beetle a true cyborg and directly implanted the generators to the insect’s flight muscles. That’s enough power to run the onboard neuro-hardware needed to manipulate the beetles--which means basically the ability to tell a Green June beetle to fly depends on the power generated from flight.
That’s pretty cool, considering DARPA and the rest of the cyborg insect research establishment has a variety of roles in mind for the sensor laden drone insects of the future, including search and rescue, intelligence and surveillance, environmental monitoring and the like.
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Video: HTV-2 in Mach-20 Flight, Just Minutes Before Autonomously Aborting its Mission
Back on August 11th , then lost, its Falcon hypersonic vehicle, also known as HTV-2. Today we found it. Not the actual glider, but a video of it streaking through the sky over the Pacific Ocean as captured by a crew member aboard a tracking ship. And as you can see in this video, it is indeed moving fast.
For those out of the loop on this, HTV-2 is an unmanned hypersonic glider meant to test the boundaries of hypersonic flight. HTV-2 was traveling at Mach 20--that’s 20 times the speed of sound--when an as-yet unexplained flight anomaly caused the vehicle’s automated systems to kick in and put the thing into a into the Pacific. By the time that happened, three minutes into HTV-2’s independent flight, it was somewhere well on its way to Hawaii. It started at Vandenberg AFB in California.
In the video above, you can see a white contrail entering the left of the frame. That’s not just the HTV-2, but the third stage of the Minotaur 4 rocket that carried HTV-2 to the edge of space. From there, if you look very closely you can see HTV-2 separate from the rocket stage (it’s a really faint dot) and begin its aerodynamically stable hypersonic flight, in which it hits its objective speed of Mach 20.
Can’t see it? Try the video below.
Saw it that time, didn't you?
DARPA Fills Us In On HTV-2′s Semi-Successful Flight and Very Successful Crash
Now to HTV-2. Sort of.
HTV-2 separated from its Minotaur carrier rocket successfully and entered the descent phase of its flight with all systems looking nominal. But somewhere “post-perigee”--where it was supposed to start climbing again--HTV-2 encountered a flight anomaly that caused its autonomous systems to initiate a controlled termination of the flight. That is, the computer took over and crashed the hypersonic vehicle into the Pacific just as it was designed to do. Per DARPA director Regina Dugan via press release:
According to a preliminary review of the data collected prior to the anomaly encountered by the HTV-2 during its second test flight, HTV-2 demonstrated stable aerodynamically controlled Mach 20 hypersonic flight for approximately three minutes. It appears that the engineering changes put into place following the vehicle’s first flight test in April 2010 were effective. We do not yet know the cause of the anomaly for Flight 2.
While not ideal news, don’t miss the most important message there. HTV-2 achieved stable Mach 20 flight for about three minutes, gathering data all the way through. That’s 20 times the speed of sound. And though DARPA isn’t sure what the “anomaly” was, HTV-2 also demonstrated that its autonomous systems worked perfectly--at least according to DARPA. You can’t have a rogue hypersonic missile out there roaming the skies out of control. When something went awry, HTV-2 offed itself in the controlled manner prescribed by its engineers.
So it wasn’t a completely successful flight, but it was a successful crash. No word on where the program goes from here, but its unlikely DARPA is simply going to sit on that valuable hypersonic flight data. Expect something equally cool to be in the works in coming months.
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New Computer Chip Modeled on a Living Brain Can Learn and Remember
IBM, with help from DARPA, has built two working prototypes of a "neurosynaptic chip." Based on the neurons and synapses of the brain, these first-generation cognitive computing cores could represent a major leap in power, speed and efficiency
About a year ago, we told you about IBM’s project to map the , the most complex brain networking project of its kind. Big Blue wasn’t doing it just for the sake of science — the goal was to reverse-engineer neural networks, helping pave the way to cognitive computer systems that can think as efficiently as the brain. Now they’ve made just such a system — two, actually — and they’re calling them neurosynaptic chips.
Built on 45 nanometer silicon/metal oxide semiconductor platform, both chips have 256 neurons. One chip has 262,144 programmable synapses and the other contains 65,536 learning synapses — which can remember and learn from their own actions. IBM researchers have used the compute cores for experiments in navigation, machine vision, pattern recognition, associative memory and classification, the company says. It’s a step toward redefining computers as adaptable, holistic learning systems, rather than yes-or-no calculators.
“This new architecture represents a critical shift away form today’s traditional von Neumann computers, to extremely power-efficient architecture,” Dharmendra Modha, project leader for IBM Research, said in an interview. “It integrates memory with processors, and it is fundamentally massively parallel and distributed as well as event-driven, so it begins to rival the brain’s function, power and space.”
You can read up on Von Neumann architecture , but essentially it is a system with two data portals, which are shared by the input instructions and output data. This creates a bottleneck that will fundamentally limit the speed of memory transfer. IBM’s system eliminates that bottleneck by putting the circuits for data computation and storage together, allowing the system to compute information from multiple sources at the same time with greater efficiency. Also like the brain, the chips have synaptic plasticity, meaning certain regions can be reconfigured to perform tasks to which they were not initially assigned.
IBM’s long-term goal is to build a chip system with 10 billion neurons and 100 trillion synapses that consumes just one kilowatt-hour of electricity and fits inside a shoebox, Modha said.
The project is funded by DARPA’s SyNAPSE initiative, and IBM just completed phases 0 and 1. IBM’s project, which involves collaborators from Columbia University, Cornell University, the University of California-Merced and the University of Wisconsin-Madison, just received another $21 million in funding for phase 2, the company said.
Computer scientists have been working for some time on systems that can emulate the brain’s massively parallel, low-power computing prowess, and they’ve made several breakthroughs. Last year, computer engineer Steve Furber described a that consists of tens of thousands of cellphone chips.
The most notable computer-brain achievements have been in the field of . As their name implies, a memory resistor can “remember” the last resistance that it possessed when current was flowing through it — so after current is turned back on, the resistance of the circuit will be the same. We will not attempt to delve too deeply here, but this basically makes a system much more efficient.
Hewlett-Packard has been since first describing them in 2008, and has also been part of the SyNAPSE project. Last spring, HP engineers described a titanium dioxide memristor that uses low power.
For a brain-based computer system, memristors can function as a computer analogue for a synapse, which also stores information about previous data transfer. IBM's chip doesn't use a memristor architecture, but it does integrate memory with computation power — and it uses computer neurons and axons to do it. The building blocks are simple, but the architecture is unique, said Rajit Manohar, associate dean for research and graduate studies in the engineering school at Cornell.
"When a neuron changes its state, the state it is modifying is its own state, not the state of something else. So you can physically co-locate the circuit to do the computation, and the circuit to store the state. They can be very close to each other, so that cooperation becomes very efficient," he said.
Modha said it is just a new way to store memory.
"A bit is a bit is a bit. You could store a bit in a memristor, or a phase-change memory, or a nano-electromechanical switch, or SRAM, or any form of memory that you please. But by itself, that does not a complete architecture make," Modha said. "It has no computational capability."
But this new chip does have that power, he said. It integrates memory with processor capability on a typical SOI-CMOS platform, using traditional transistors in a new design. Along with integrated memory to stand in for synapses, the neurosynaptic “core” uses typical transistors for input-output capability, i.e. neurons.
This new architecture will not replace traditional computers, however. “Both will be with us for a long time to come, and continue to serve humanity,” Modha predicted.
The idea is that future powerful chips based on this brain-network design will be able to ingest and compute information from multiple inputs and make sense of it all — just like the brain does.
A cognitive computer monitoring the oceans could record and compute variables like temperature, wave height and acoustics, and decide whether to issue tsunami or hurricane warnings. Or a grocer stocking shelves could use a special glove that monitors scent, texture and sight to flag contaminated produce, Modha said. Modern computers can’t handle that level of detail from so many inputs, he said. But our brains do it all the time — grab a rotting peach, and your senses of touch, smell and sight work in concert instantaneously to determine that the fruit is bad.
To do this, the brain uses electrical signals between some 150 trillion synapses, all while sipping energy — our brains need about 20 watts to function. Understanding how this works is key to building brain-based computers, which is why IBM has been working with neuroscientists to study monkey and . That research is progressing, Modha said.
But it will be quite some time before computer chips can truly match the ultra-efficient computational powerhouses that nature gave us.
Sneak Preview: Military’s Maple-Seed-Inspired Drone, Plus More to Come at UAV Show Next Week
The asymmetric UAV is modeled after maple seeds, called samara, that fly off trees and twirl through the air with the . Originally, the SAMARAI was envisioned as a that could deliver a 2-gram payload and send back streaming video, but that has since changed to a much bigger, whining drone.
The current model has just two moving parts, allowing it to fly with a cyclic lift motion like that of a helicopter. It does have a camera on board, and it can be operated via remote control or a tablet computer, the AP says. Check out a video of it below.
The Samarai is just one of a suite of new unmanned vehicles that will be on display next week in Washington, D.C., at the convention of the . PopSci will be reporting from this year’s convention, so check back regularly starting Aug. 16 for updates on the latest in unmanned vehicles, from the ground to the air.
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