What Boston Dynamics’ Rolling ‘Handle’ Robot Really Means

https://www.wired.com/story/what-boston-dynamics-rolling-handle-robot-really-means

For internet-goers, Boston Dynamics is that company that uploads insane videos of the humanoid Atlas robot doing backflips, of four-legged SpotMini opening doors and fighting off stick-wielding men, and as of last week, of a Segway-on-mescaline called Handle jetting around picking up and stacking boxes with a vacuum as its arm. For journalists and industry watchers, however, Boston Dynamics is that company that almost never talks about where all of this work is ultimately headed.

That’s beginning to change. The company is now teasing its ambitions as the four-legged SpotMini nears its commercial release. Today, Boston Dynamics is getting even more explicit about its vision with an announcement that it’s acquired a Silicon Valley startup called Kinema Systems, which builds vision software that helps industrial robot arms manipulate boxes. This acquisition is giving the Handle robot the gray matter it needs to follow SpotMini to market. What for years has been fodder for internet video gold is now taking shape as a unified vision of the robotic future.

One of the biggest obstacles holding robots back has been their limited perception. We humans enjoy a rich constellation of senses that help us navigate our surroundings. Robots need the same, lest they destroy themselves. Go to pick up a box, for example, and you as a human probably don’t think deeply about the lighting, and how it may cast shadows that throw off your hand placement.

Kinema’s software—which is robot-agnostic, meaning it already works on a range of robots beyond Handle—helps the machine through all these challenges. “Their system is able to look at a stack of boxes,” says Michael Perry, vice president of business development at Boston Dynamics, “and despite how ordered or disordered the boxes are, or the markings on top, or the lighting conditions, they’re able to figure out which boxes are discrete from each other and to plan a path for grabbing the box.”

That’s a huge part of what Handle, a robot designed to work in warehouses, needs to do. But the robot also relies on its overall shape to do its (soon-to-be) job. This is where BD’s larger strategy gets even more interesting: Although Handle, Atlas, and SpotMini look almost nothing alike, they are in fact intimately connected.

“Handle isn’t entirely different from Atlas,” says Boston Dynamics boss Marc Raibert. Indeed, a video of Atlas three years ago showed the robot picking up boxes with two arms that ended in stubs, arms that Handle wielded in its own video a year later. The challenges of bipedal locomotion are largely the same, namely the balance problems that a four-legged robot like SpotMini doesn’t share, as are the challenges of manipulation with two arms, which SpotMini (being the dog to Atlas’ human form) also doesn’t share.

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But this is the beauty of robots. You can iterate on their shapes to tailor them to different tasks and environments. Atlas walks on two legs and Handle rolls on two wheels, but either way, that bipedal locomotion cuts down on the robots’ footprint. “If it was a four-wheeled robot, it would have to be much larger in order to get that level of reach and lift boxes,” says Perry. “So this is a robot that’s designed to go into human-purposed environments and still be able to complete a task.”

The reason BD is able to riff on its robot shapes with relative ease boils down to one big thing: repurposed software.

When you think Boston Dynamics, you probably don’t first marvel at the code that’s running these machines—BD is famous for its hardware. But Raibert takes issue with that characterization. “I think it’s a misconception that we’re a hardware company,” he says. “The only reason any of our machines do what they do is because of the controls and perception and the systems that coordinate with the hardware. It’s just that our hardware is so strong, that’s what makes us look like that.”

Someone, after all, has to program Atlas to do those backflips. SpotMini needs software to autonomously navigate its world. And two-wheeled Handle needs finely tuned control algorithms to keep from falling on its face. BD works out these algorithms across its platforms. “There’s a lot of stuff that flows,” says Raibert. “The next group uses a lot and then creates their own stuff, and then that flows back.”

With a cognitive core that’s developed over time and shared across platforms, BD has been able to devote energy to honing each of its robots’ specialties. In SpotMini’s case, it’s about becoming an expert at navigating challenging terrain. “When we’ve been looking at applications for Spot,” Perry says, “we’re very careful to screen out tasks we think a wheeled or tracked robot could do even better.” SpotMini is a good match for environments that transition from one terrain to another. “So street to curb, stairs, lips between rooms,” he says.

A relatively structured environment like a warehouse, on the other hand, tends to be a great place for a wheeled robot. Clutter can make such places chaotic, sure, but in general the robot can rely on a flat, smooth surface to glide across. In such an environment, wheels are often more efficient than legs: Handle can manage four hours of operation on a charge, whereas with SpotMini it’s more like an hour and a half. And Handle could potentially go even longer. Swinging around Handle’s backside is a counterweight that could hold even more batteries, Raibert says.

The previous iteration of Handle had stump arms instead of a single vacuum arm. Also notice that the bulk of the weight is in the torso, whereas the new version has a swinging counterweight on its rear end to balance.

Boston Dynamics

Plus, a human worker can wield Handle as a unique kind of tool. “It’s also got a mode where it can squat down and you can manually wheel it around,” says Raibert. To be clear, BD doesn’t intend Handle to be a particularly collaborative robot—it’ll likely work in isolation from humans, unloading pallets autonomously while humans take care of other tasks in the warehouse. At least, that’s the plan.

Accordingly, Handle is a bit simpler as far as perception is concerned. It’s got one camera to localize itself in space, another for obstacle avoidance, and another looking for the best place to grab a box. SpotMini, on the other hand, “is trying to be a little more general purpose,” says Raibert. “So we have cameras looking in all directions.”

With Handle stacking boxes and SpotMini wandering more widely, perhaps inspecting oil and gas operations, Atlas’ destiny might lie somewhere in between. Its legs allow it to stomp over difficult terrain, but its humanoid form might make it better suited to navigating indoor spaces designed for humans. It could one day, for instance, climb ladders, which would befuddle Handle and SpotMini.

But all that hardware we’ve been marveling at over the years has been a kind of illusion—sophisticated machinery, to be sure, that obscures equally sophisticated software. With the acquisition of Kinema Systems, BD not only bolsters the software side of things, it can now sell that system for use in warehouse robots it doesn’t manufacture itself.

Oh, and it means Boston’s most famous robotics company now has a base of operations on the West Coast. “We’ll have machines out there, but they’ll be for the development of the applications and perception and software,” says Raibert. “Our current plan is to keep the core of the hardware engineering here. We’ll see how that evolves.”


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via Wired Top Stories https://ift.tt/2uc60ci

April 2, 2019 at 02:09PM

See-Through Film Rejects 70 Percent of Incoming Solar Heat

https://www.techbriefs.com/component/content/article/5-tb/techbriefs/materials/34166-see-through-film-rejects-70-percent-of-incoming-solar-heat?Itemid=690

A heat-rejecting film was developed that could be applied to a building’s windows to reflect up to 70 percent of the Sun’s incoming heat. The film remains highly transparent below 32 °C (89 °F). Above that temperature, the film acts as an “autonomous system” to reject heat. If every exterior-facing window in a building were covered in this film, air conditioning and energy costs could drop by 10 percent.

via NASA Tech Briefs https://ift.tt/2BVPq4O

April 2, 2019 at 04:55PM

Watch a self-driving car navigate with just cameras and basic GPS

https://www.engadget.com/2019/04/03/wayve-self-driving-car-navigates-without-lidar-or-maps/

Self-driving cars currently need a lot of hand-holding to get around, with even Waymo’s machines relying on lidar, custom rules and highly detailed maps to know exactly where to go. Wayve, however, wants driverless vehicles with more independence. It just showed a prototype autonomous vehicle (a modified Renault Twizy) driving around Cambridge, UK using only cameras and basic GPS directions from a phone. It had never seen the roads before, and was only running on 20 hours of training data — it didn’t even know to drive on the left side of the road or to slow down at intersections where it didn’t have the right of way.

The trick, according to Wayve, is the approach to the driving AI. It learns to drive like a human through imitation and reinforcement, using computer vision to follow the intended route. It also uses the input data to learn only those features that are most relevant to control. This not only helps it get up to snuff quickly, but dramatically lightens the computing workload. The self-driving AI can run on the "equivalent" of a modern laptop, Wayve said. Existing self-driving cars frequently need extensive computing power that can be expensive and heavy.

The technology isn’t about to see everyday use. Wayve’s demo saw the Twizy putting around at low speeds in relatively light traffic. While it did handle some complicated scenarios, there’s a certain tentativeness to the vehicle’s behavior. The human occupant had to take over to park, too. Nonetheless, it’s one step closer to autonomous rides that can navigate unfamiliar roads and unexpected situations with relative ease.

Via: TechCrunch

Source: Wayve

via Engadget http://www.engadget.com

April 3, 2019 at 10:30AM

Intel’s new assault on the data center: 56-core Xeons, 10nm FPGAs, 100gig Ethernet

https://arstechnica.com/?p=1485223

Left to right: Cascade Lake Xeon AP, Cascade Lake Xeon SP, Broadwell Xeon D-1600, and up front Optane DC Persistent Memory.
Enlarge /

Left to right: Cascade Lake Xeon AP, Cascade Lake Xeon SP, Broadwell Xeon D-1600, and up front Optane DC Persistent Memory.

Intel today launched a barrage of new products for the data center, tackling almost every enterprise workload out there. The company’s diverse range of products highlights how today’s data center is more than just processors, with network controllers, customizable FPGAs, and edge device processors all part of the offering.

The star of the show is the new Cascade Lake Xeons. These were first announced last November, and at the time a dual-die chip with 48 cores, 96 threads, and 12 DDR4 2933 memory channels was going to be the top spec part. But Intel has gone even further than initially planned with the new Xeon Platinum 9200 range: the top-spec part, the Platinum 9282, pairs two 28 core dies for a total of 56 cores and 112 threads. It has a base frequency of 2.6GHz, a 3.8GHz turbo, 77MB of level 3 cache, 40 lanes of PCIe 3.0 expansion, and a 400W power draw.

The new dual die chips are dubbed “Advanced Performance” (AP) and slot in above the Xeon SP (“Scalable Processor”) range. They’ll be supported in two socket configurations for a total of four dies, 24 memory channels, and 112 cores/224 threads. Intel does not plan to sell these as bare chips; instead, the company is going to sell motherboard-plus-processor packages to OEMs. The OEMs are then responsible for adding liquid or air cooling, deciding how densely they want to pack the motherboards, and so on. As such, there’s no price for these chips, though we imagine it’ll be somewhere north of “expensive.”

Model Cores/Threads Clock base/boost/GHz Level 3 cache/MB TDP/W Price
Platinum 9282 56/112 2.6/3.8 77.0 400 $many
Platinum 9242 48/96 2.3/3.8 71.5 350 $many
Platinum 9222 32/64 2.3/3.7 71.5 250 $many
Platinum 9221 32/64 2.1/3.7 71.5 250 $many

As well as these new AP parts, Intel is offering a full refresh of the Xeon SP line. The full Cascade Lake SP range includes some 60 different variations, offering different combinations of core count, frequency, level 3 cache, power dissipation, and socket count. At the top end is the Xeon Platinum 8280, 8280M, and 8280L. All three of these have the same basic parameters: 28 cores/56 threads, 2.7/4.0GHz base/turbo, 38.5MB L3, and 205W power. They differ in the amount of memory they support: the bare 8280 supports 1.5TB, the M bumps that up to 2TB, and the L goes up to 4.5TB. The base model comes in at $10,009, with the high memory variants costing more still.

Across the full range, a number of other suffixes pop up, too; N, V, and S are aimed at specific workloads (Networking, Virtualization, and Search, respectively), and T is designed for long-life/reduce-thermal loads. Finally, a few models have a Y suffix. This denotes that they have a feature called “speed select,” which allows applications to be pinned to the cores with the best thermal headroom and highest-possible clock speeds.

Cascade Lake itself is an incremental revision to the Skylake SP architecture. The basic parameters—up to 28 cores/56 threads per die, 1MB level 2 cache per core, up to 38.5MB shared level 3 cache, up to 48 PCIe 3.0 lanes, six DDR4 memory channels, and AVX-512 support—remain the same, but the details show improvement. They support DDR4-2933, up from DDR4-2666, and the standard memory supported is now 1.5TB instead of 768GB. Their AVX-512 support has been extended to include an extension called VNNI (“vector neural network instructions”) aimed at accelerating machine-learning workloads. They also include (largely unspecified) hardware fixes for most variants of the

Spectre and Meltdown attacks

.

The other big thing that Cascade Lake brings beyond Skylake is support for Optane memory. Most of the Xeon SP range (though, oddly, not the Xeon AP processors) can use Optane DIMMs built to the DDR4-T standard. Optane (also known as 3D XPoint) is a non-volatile solid-state memory technology developed by Intel and Micron. Its promise is to offer density that’s comparable to flash, random access performance that’s within an order of magnitude or two of DDR RAM, and enough write endurance that it can be used in memory-type workloads without failing prematurely. It does all this at a price considerably lower than DDR4.

Intel has been talking about using Optane DIMMs for memory-like tasks for some time, but only today is it finally launching, as Optane DC Persistent Memory. Systems can’t use Optane exclusively—they’ll need some conventional DDR4 as well—but by using the combination they can be readily equipped with vast quantities of memory, using 128, 256, or 512GB Optane DIMMs.

Intel Optane DC Persistent Memory.
Enlarge /

Intel Optane DC Persistent Memory.

Intel

Applications unaware of non-volatile memory can use the Optane and DDR4 as a single giant pool of memory. Behind the scenes, the DDR4 will cache the Optane, and the overall effect will be simply that a machine has an awful lot of memory that’s a little slower than regular memory. Alternatively, applications can be written to explicitly use non-volatile memory and will have direct access to the Optane, using it as a kind of giant, randomly accessible, high-speed disk.

To alleviate any concerns about endurance, Intel is offering a 5-year warranty for Optane DC Memory, even for parts that have been running at their peak write performance for the entire five years.

Intel also announced some refreshes to the Xeon D systems-on-chips first launched in 2015. In 2015, Intel launched the Broadwell-based Xeon D 1500 line. Last year, these were joined by the Skylake SP-based Xeon D 2100 line. The 2100 line offered a significant upgrade in performance and memory capacity but with much higher power draws, too.

Today comes the Xeon D 1600 line, direct replacements for the 1500 parts. Surprisingly, these new 1600 parts continue to use the same Broadwell architecture as their predecessors; they’re aimed at the same kinds of storage and networking workloads, with two to eight cores/16 threads, up to 128GB RAM, and power draws between 27 and 65W.

As well as the processor cores, they include (depending on which exact model you look at) four 10GbE Ethernet controllers, Intel Quick Assist Technology acceleration of compression and encryption workloads, six SATA 3 channels, four each of USB 3.0 and 2.0 ports, 24 lanes of PCIe 3.0, and eight lanes of PCIe 2.0.

Intel 800-series Ethernet controller.
Enlarge /

Intel 800-series Ethernet controller.

Intel

Announced today but coming in the third quarter is a new Intel Ethernet controller. The 800 series, codenamed Columbiaville, will support 100Gb Ethernet. These controllers are rather more programmable than your typical Ethernet controller, with customizable software-controlled packet parsing happening within the Ethernet controller itself. That means the chip can send a packet for further processing, reroute it to a different destination, or do whatever an application needs, all without the involvement of the host processor at all. The controllers also support application-defined queues and rate limits, so complex application-specific prioritization can be enforced.

For its final data center offering, Intel announced the Agilex FPGA (field programmable gate array—a processor that can have its internal wiring reconfigured on the fly), built using the company’s 10nm process. These chips offer up to 40TFLOPS of number-crunching performance and enable developers to build a wide range of application-specific accelerators. The FPGAs will sport a range of optional capabilities, such as containing four ARM Cortex-A53 cores, PCIe generation 4 or 5, DDR4, DDR5, and Optane DC Persistent memory, with an option for HBM high bandwidth memory mounted on-chip and cache coherent interconnects to attach them to Xeon SP chips.

For machine-learning workloads, they’ll support a range of low-precision integer and floating point formats. Further customization will come from the ability to work with Intel and directly embed custom chiplets into the FPGAs.

Intel Agilex FPGA model.
Enlarge /

Intel Agilex FPGA model.

Intel

Over the last few years, FPGAs have become increasingly common, especially in the cloud data centers operated by the likes of Microsoft, Google, and Amazon, as they offer a useful midpoint between the enormous flexibility of software-based computation and the enormous performance of hardware-based acceleration; they offer flexible acceleration of things like networking, encryption, and machine-learning workloads in a manner that is readily upgraded and altered to adapt to new algorithmic requirements and models.

Intel plans to have these available from the third quarter.

via Ars Technica https://arstechnica.com

April 2, 2019 at 05:26PM