The Adorable Robot Spot, Now In Affordable Form

If you’ve been following the Boston Dynamics project Spot, you’ve seen its capabilities and how we’re starting to see it being used in public more since its official release last year. But in a true display of how hobbyist electronics have been evolving and catching up with the big companies over the past few years, [Miguel Ayuso Parrilla] shows us his own take on the walking robot with CHOP, one of the finalists in this year’s Hackaday Prize.

CHOP is a DIY quadruped robot that works much in the same way as Spot, although in a smaller form-factor and, perhaps most impressive of all, a bill of materials that can be all acquired for under $500. The entire project is open source, meaning that anyone can built their own version of it with off-the-shelf parts and some 3D printing. If you can’t get the hardware however, you can still play with the PyBullet simulation of the mechanics that were used during the debugging process.

Running the show are two main components, a Raspberry Pi 4B and an Arduino Mega. While the Mega interfaces with the servo controllers and provides filtering for sensors like the inertial measurement unit, the Pi takes all that data in and uses a series of Python scripts in order to determine the gait of the robot and which way the servos should move through an inverse kinematics model. To control the direction in which the body of the robot should accelerate, a Bluetooth remote controller sends commands to the Raspberry Pi.

We’re excited to see home-grown projects rise to this level of complexity, which would be mostly unheard of a few years ago in the maker scene, and only presented by large tech companies with tons of money to spend on research and development. There are other quadruped robots to inspire yourself on than Spot though, like this one with a spherical design and fold-out legs. Check this one in action after the break.

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Jetson Nano Robot

[Stevej52] likes to build things you can’t buy, and this Jetson Nano robot falls well within that category. Reading the project details, you might think [Stevej52] drinks too much coffee. But we think he is just excited to have successfully pulled off the Herculean task of integrating over a dozen hardware and software modules. Very briefly, he is running Ubuntu and ROS on the PC and Nano. It is all tied together with Python code, and is using Modbus over IP to solve a problem getting joystick data to the Nano. We like it when existing, standard protocols can be used because it frees the designer to focus more on the application. Modbus has been around for 40 years, has widespread support in many languages and platforms.

This is an ongoing project, and we look forward to seeing more updates and especially more video of it in action like the one found below. With the recent release of a price-reduced Jetson Nano, which we covered last week, this might be an excellent project to take on.

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The Ever-Accelerating Automation Of Fast Food

In the fast food industry, speed is everything. The concept has never just been about cooking quickly. Players in this competitive space spend huge fortunes every year on optimizing every aspect of the experience, from ordering, to queueing, to cleaning up afterwards. And while fast food restaurants are major employers worldwide, there’s always been a firm eye cast over the gains that automation has to offer.

Flipping Burgers

In the West, fast food most commonly brings burgers to mind. Preparing a quality burger requires attention to the grade of meat, fat content, as well as the preparation steps before it hits the grill. Then it’s all about temperature and time, and getting just the right sear to bring out the natural flavors of the beef. While a boutique burger joint will employ a skilled worker to get things just right, that doesn’t fly for fast food. Every order needs to be preparable by whichever minimum-wage worker got the shift, and be as repeatable as possible across entire countries, or even the world, to meet customer expectations.

Flippy ROAR (Robot On A Rail) at work on the fryers in a White Castle in Chicago.

In their efforts to improve efficiency, White Castle have taken the bold step of installing a robotic burger flipper, imaginitively named Flippy. Built by Miso Robotics, the robot hangs from a ceiling rail to minimise the space taken up in the kitchen area. Based on a Fanuc robot arm, the system uses artificial intelligence to manage kitchen resources, Flippy is capable of managing both the grill and fryers together to ensure fries don’t get cold while the burgers are still cooking, for example. Currently undergoing a trial run in Chicago, White Castle has ambitions to roll the technology out to further stores if successful.

We’ve seen other robotic burger systems before, too. In late 2018, our own [Brian Benchoff] went down to check out Creator, which cooks and assembles its burgers entirely by machine. Despite suspicions about the business model, Creator have persisted until the present day with their unique blend of technology and culinary arts. Particularly impressive were their restaurant modifications in the face of COVID-19. The restaurant received an overhaul, with meals being robotically prepared directly in a take-out box with no human contact. Take-out meals are double-bagged and passed to customers through an airlock, with a positive-pressure system in the restaurant to protect staff from the outside world.

Pizzabots

Pizza is a staple food for many, with high demand and a stronger dependence on delivery than other fast food options. This has led to the industry exploring many avenues for automation, from preparation to order fulfillment.

In terms of outright throughput, Zume were a startup that led the charge. Their system involves multiple robots to knead dough, apply sauce and place the pie in the oven. Due to the variable nature sizes and shapes of various toppings, these are still applied by humans in the loop. Capable of turning out 120 pizzas per hour, a single facility could compete with many traditional human-staffed pizza shops. They also experimented with kitchens-on-wheels that use predictive algorithms to stock out trucks that cook pizzas on the way to the customer’s door. Unfortunately, despite a one-time $4 billion USD valuation, the startup hit a rocky patch and is now focusing on packaging instead.

Picnic aim to make lots of pizza, fast. Their business model involves working directly with existing restaurants, rather than creating their own fast-food brand from scratch.

Picnic have gone further, claiming an output rate of up to 300 twelve-inch pies an hour. The startup aims to work with a variety of existing pizza restaurants, rather than striking out as their own brand. One hurdle to overcome is the delivery of a prepared pizza into the oven. There are many varieties and kinds of pizza oven used in commercial settings, and different loading techniques are required for each. This remains an active area of development for the company. The company has a strong focus on the emerging ghost kitchen model, where restaurants are built solely to fulfill online delivery orders, with no dining area.

Domino’s is one of the largest pizza companies in the world, and thus far have focused their efforts on autonomous delivery. The DRU, or Domino’s Robotic Unit, was launched to much fanfare, promising to deliver pizzas by a small wheeled robotic unit. Equipped with sensors to avoid obstacles and GPS navigation, the project has not entered mainstream service just yet. However, between this and the multitude of companies exploring drone delivery, expect to see this become more of a thing in coming years.

Despite the marketing sizzle, the DOM Pizza Checker does not project holograms.

A more immediate innovation from Domino’s has been the DOM Pizza Checker. With customer complaints about pizza quality plaguing the chain, the pizza checker is an AI-powered visual system. It’s responsible for determining if the correct pizza has been made, with the right toppings and good distribution. An impressive practical use of AI imaging technology, it sounds an alarm if the pizza isn’t up to scratch, prompting it to be remade. However, it has come under scrutiny as a potential method to harass franchisees and workers. Additionally, the limitations of the system mean that Domino’s are still perfectly capable of turning out a bad pizza on occasion.

Other Efforts

One of the most visible examples of fast food automation is the widespread adoption of order kiosks by McDonalds, which kicked off in earnest in 2015. The majority of stores in the US now rely on these to speed up the ordering process, while also enabling more customization for customers with less fuss. Over-the-counter ordering is still possible at most locations, but there’s a heavy emphasis on using the new system.

McDonald’s automated beverage dispenser will be a familiar sight to many. Considered a great help when it works, and a great hindrance when it jams, spills, or simply shuts down.

In general, online ordering and delivery has become the norm, where ten years ago, the idea of getting McDonalds delivered was considered magical and arcane. This writer made seven attempts to take advantage of an early version of the service in China in 2015, succeeding only once, largely due to a lack of understanding of addresses written in non-Latin characters. However, due to the now-ubiquitous nature of services like Ubereats, Postmates, and Menulog, it’s simple for any restaurant to largely automate their ordering and fulfillment process, and reach customers at a distance from their brick-and-mortar locations.

Other efforts are smaller in scope, but contribute to great efficiency gains back-of-house. McDonalds and other chains have widely adopted automated beverage systems. Capable of automatically dispensing cups and the requisite fluids, they take instructions directly from the digital ordering system and take the manual labor out of drink preparation. They’re also great at slightly underfilling the cups, in a way that any human would consider incredibly rude.

Conclusion

Robots in the fast-food kitchen stand to reduce or eliminate tedious, repetitive work. Robots don’t get sick, and less human labour means fewer rostering hassles. It seems to be a foregone conclusion that more automation is on the way, and while some startups may falter, others will surely succeed. Your next meal may just yet be entirely prepared by a robot, even if it’s still delivered by a tired grad student on a moped. Come what may!

 

SoftBank Robots Pinch Hit For Baseball Cheerleaders

Grand venues of spectacle to entertain audiences has long been a part of history, but such tradition is highly problematic at the moment in the light of the pandemic. Some sports leagues are testing the waters with a soft restart by playing only to a broadcast audience, leaving the stadium empty. Many experiments are in progress trying to liven up an empty stadium and this is where SoftBank saw an opportunity: as a multinational conglomerate that has both a baseball team and a robotics division, they called a team of robots to cheer-leading duty.

Some clips of the cheerleading squad in action have started circulating. A few people may greet the sight with an indifferent shrug, but most tend to fall to an extreme: either finding them hilarious or react with horror. It is only natural to have a strong reaction to such a jarring sight.

Spot was only available for sale recently, and we admit this was not the type of task that came to our minds. Pepper has a longer track record and this is not Pepper’s first baseball game. The humanoid robot has been around long enough to raise questions about a robot’s role in society from unionization to sex work. We haven’t made much progress answering those questions, and now we have even more questions that the lightweight SoftBank Robotics press release (in Japanese) didn’t try to answer.

When people fret about “robots taking our jobs” the conversation doesn’t usually involve sports team cheerleaders, yet here we are. Welcome to the future.

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A Reason To Code

My son is just getting to the age that puts him in the crosshairs of all of the learn-to-code toys. And admittedly, we’ve been looking at some of those Logo-like toys where you can instruct a turtle-bot to make a few moves, and then to repeat them. After all, if breaking down a problem into sub-problems and automating the repetition isn’t the essence of programming, I don’t know what is.

But here’s the deal: I think drawing ‘bots are cooler than he does. If you ask a kid “hey, do you want a car that can draw?” that’s actually pretty low on the robot list. I’m not saying he won’t get into it once he’s got a little bit more coding under his belt and he can start to make it do fun things, but by itself, drawing just isn’t all that impressive. He can draw just fine, thank-you-very-much.

Meanwhile, I was making a robot arm. Or rather, I started up on yet another never-to-be-completed robot arm. (Frankly, I don’t know what I would do with a robot arm.) But at least I started with the gripper and wrist. Now that’s pretty cool for a kid, but the programming is waaaay too complicated. So I pulled the brains out and hooked up the servos to an RC plane remote. Just wiggling the thing around, duct-taped to the table, got him hooked. And this weekend, we’re building a remote controlled cherry-picker arm to put on a pole, because cherries are in season. His idea!

So no coding. He’s a little too young anyway, IMO. But silly little projects like these, stored deep in his subconscious, will give him a reason to program in the future, will make it plainly obvious that knowing how to program is useful. Now all I need is a reason to finish up a robot arm project…

The Birth Of The Modern Robot

When Isaac Asmiov was writing I, Robot, the field of robotics was still in its infancy. As he notes in The Complete Robot, as the field began to mature, it started showing signs of conforming to the popular ideas held by science fiction writers about what robotics ought to be. Notions of humanoid robots, the functions that robots would have in domestic settings, even the ethical quandaries that AI ethicists face today were all themes of early sci-fi writers.

The idea of a robot – at least of automata – predates the field of robotics. The idea of an independent automata may have existed as early as the ancient Egyptians Chinese, and Greeks, who attempted to build self-operated machines that resembled animals and humans. Myths of clay golems in Jewish legends and clay giants in Norse legends perpetuated the idea of an artificial being that could mimic the actions of living creatures. A 400 BC myth from Crete spoke of a man of bronze who guarded their island from pirates.

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5G Is For Robots

Ecclesiastes 1:9 reads “What has been will be again, what has done will be done again; there is nothing new under the sun.” Or in other words, 5G is mostly marketing nonsense; like 4G, 3G, and 2G was before it. Let’s not forget LTE, 4G LTE, Advance 4G, and Edge.

Just a normal everyday antenna array in a Seattle parking garage.

Technically, 5G means that providers could, if they wanted to, install some EHF antennas; the same kind we’ve been using forever to do point to point microwave internet in cities. These frequencies are too lazy to pass through a wall, so we’d have to install these antennas in a grid at ground level. The promised result is that we’ll all get slightly lower latency tiered internet connections that won’t live up to the hype at all. From a customer perspective, about the only thing it will do is let us hit the 8Gb ceiling twice as faster on our “unlimited” plans before they throttle us. It might be nice on a laptop, but it would be a historically ridiculous assumption that Verizon is going to let us tether devices to their shiny new network without charging us a million Yen for the privilege.

So, what’s the deal? From a practical standpoint we’ve already maxed out what a phone needs. For example, here’s a dirty secret of the phone world: you can’t tell the difference between 1080p and 720p video on a tiny screen. I know of more than one company where the 1080p on their app really means 640 or 720 displayed on the device and 1080p is recorded on the cloud somewhere for download. Not a single user has noticed or complained. Oh, maybe if you’re looking hard you can feel that one picture is sharper than the other, but past that what are you doing? Likewise, what’s the point of 60fps 8k video on a phone? Or even a laptop for that matter?

Are we really going to max out a mobile webpage? Since our device’s ability to present information exceeds our ability to process it, is there a theoretical maximum to the size of an app? Even if we had Gbit internet to every phone in the world, from a user standpoint it would be a marginal improvement at best. Unless you’re a professional mobile game player (is that a thing yet?) latency is meaningless to you. The buffer buffs the experience until it shines.

So why should we care about billion dollar corporations racing to have the best network for sending low resolution advertising gifs to our disctracto cubes? Because 5G is for robots.

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