High-Style Ball Balancing Platform

February 2, 2019 by Dan Maloney 14 Comments

If IKEA made ball-balancing PID robots, they’d probably look like this one.

This [Johan Link] build isn’t just about style. A look under the hood reveals not the standard, off-the-shelf microcontroller development board you might expect. Instead, [Johan] designed and built his own board with an ATmega32 to run the three servos that control the platform. The entire apparatus is made from a dozen or so 3D-printed parts that interlock to form the base, the platform, and the housing for the USB webcam that’s perched on an aluminum tube. From that vantage point, the camera’s images are analyzed with OpenCV and the center of the ball is located. A PID loop controls the three servos to center the ball on the platform, or razzle-dazzle it a little by moving the ball in a controlled circle. It’s quite a build, and the video below shows it in action.

We’ve seen a few balancing platforms before, but few with such style. This Stewart platform comes close, and this juggling platform gets extra points for closing the control loop with audio feedback. And for juggling, of course.

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A 3D Printed Robotic Chariot For Your Phone

February 1, 2019 by Tom Nardi 6 Comments

As we’ve said many times in the past, the wide availability of low-cost modular components has really lowered the barrier to entry for many complex projects which previously would have been nigh-on impossible for the hobbyist to tackle. The field of robotics has especially exploded over the last few years, as now even $100 can put together a robust robotics experimentation platform which a decade ago might have been the subject of a DARPA grant.

But what if you want to go even lower? What’s the cheapest and easiest way to put together something like a telepresence robot? That’s exactly what [Advance Robotics] set out to determine with their latest project, and the gadget’s final form might be somewhat surprising. Leveraging the fact that nearly everyone has a device capable of video calls in their pocket, the kit uses simple hardware and 3D printed components to produce a vehicle that can carry around a smartphone. With the phone providing the audio and video link, the robot only needs to handle rolling around in accordance with the operators commands.

The robot chassis consists of a few simple 3D printed components, including the base which holds the phone and electronics, the wheels, and the two rear “spoons” which are used to provide a low-friction way of keeping the two-wheeled device vertical. To get it rolling, two standard DC gear motors are bolted to the sides. With the low cost of printer filament and the fact that these motors can be had for as little as $2 online, it’s hard to imagine a cheaper way to get your electronics moving.

As for the electronics, [Advance Robotics] is using the Wemos D1 Mini ESP8266 development board along with L298N motor controller, another very low-cost solution. The provided source code pulls together a few open source libraries and examples to provide a simple web-based user interface which allows the operator to connect to the bot from their browser and move it around with just a few clicks of the mouse.

If you like the idea of printing a rover to explore your living room but want something a bit more advanced, we’ve seen printable robotics platforms that are sure to meet your needs, no matter what your skill level is.

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This 3D Printer Is Soft On Robots

January 30, 2019 by Al Williams No comments

It always seems to us that the best robots mimic things that are alive. For an example look no further than the 3D printed mesh structures from researchers at North Carolina State University. External magnetic fields make the mesh-like “robot” flex and move while floating in water. The mechanism can grab small objects and carry something as delicate as a water droplet.

The key is a viscous toothpaste-like ink made from silicone microbeads, iron carbonyl particles, and liquid silicone. The resulting paste is amenable to 3D printing before being cured in an oven. Of course, the iron is the element that makes the thing sensitive to magnetic fields. You can see several videos of it in action, below.

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Badland Brawler Lets Arduino Tackle Terrain

January 27, 2019 by Al Williams 6 Comments

For an electronics person, building the mechanics of a robot — especially a robust robot — can be somewhat daunting. [Jithin] started with an off-the-shelf 4 wheel drive chassis to build an off-road Arduino robot he calls the Badland Brawler. The kit was a bit over $100, but as you can see in the video below, it is pretty substantial, with an enclosed frame and large mud tires.

The remaining parts include an Arduino, a battery, and a motor driver IC. The Arduino is one with WiFi (an MKR 1000, in fact) and there’s a phone app for controlling the robot.

Honestly, once you have the chassis taken care of, the rest is pretty easy. Of course, the phone app is a bit more effort, but you could replace it in a number of ways. Blynk, comes to mind, for example.

The motor drivers are easy to figure out. This would be a great platform for some sensors to allow for more autonomy. We liked how the frame had mount points for a lot of different boards and sensors and could hold everything, for the most part, inside. That’s probably a good idea for a robot which will be traversing rugged terrain.

If you do decide to roll your own app with Blynk, we’ve done it with a very different kind of robot. Four-wheel drive robots don’t have to be big, as we’ve seen in the past.

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Robot Can’t Take Its Eyes Off The Bottle

January 25, 2019 by Lewin Day 18 Comments

Robots, as we currently understand them, tend to run on electricity. Only in the fantastical world of Futurama do robots seek out alcohol as both a source of fuel and recreation. That is, until [Les Wright] and his beer seeking robot came along. (YouTube, video after the break.)

A Raspberry Pi 3 provides the brains, with an Intel Neural Compute stick plugged in as an accelerator for neural network tasks. This hardware, combined with the OpenCV image detection software, enable the tracked robot to identify objects and track their position accordingly.

That a beer bottle was chosen is merely an amusing aside – the software can readily identify many different object categories. [Les] has also implemented a search feature, in which the robot will scan the room until a target bottle is identified. The required software and scripts are available on GitHub for your perusal.

Over the past few years, we’ve seen an explosion in accelerator hardware for deep learning and neural network computation. This is, of course, particularly useful for robotics applications where a link to cloud services isn’t practical. We look forward to seeing further development in this field – particularly once the robots are able to open the fridge, identify the beer, and deliver it to the couch in one fell swoop. The future will be glorious!

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Robot’s Actions And Our Reactions

January 12, 2019 by Brian McEvoy 9 Comments

If you walk into a dog owner’s home that dog is probably going to make a beeline to see if you are a threat. If you walk into a cat owner’s home, you may see the cat wandering around, if it even chooses to grace you with its presence. For some people, a dog’s direct approach can be nerve-wracking, or even scary depending on their history and relative size of the dog. Still, these domestic animals are easy to empathize with especially if you or your family have a pet. They have faces which can convey curiosity or smug indifference but what if you were asked to judge the intent of something with no analogs to our own physical features like a face or limbs? That is what researchers at the IDC Herzliya in Israel and Cornell University in the US asked when they made the Greeting Machine to move a moon-like sphere around a planet-like sphere.

Participants were asked to gauge their feelings about the robot after watching the robot move in different patterns. It turns out that something as simple as a sphere tracing across the surface of another sphere can stir consistent and predictable emotions in people even though the shapes do not resemble a human, domestic pet, or anything but a snowman’s abdomen. This makes us think about how our own robots must be perceived by people who are not mired in circuits all day. Certainly, a robot jellyfish lazing about in the Atlantic must feel less threatening than a laser pointer with a taste for human eyeballs.

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Robot Arm Is A Fast Learner

January 11, 2019 by Brian McEvoy 3 Comments

Not long ago, machines grew their skills when programmers put their noses to the grindstone and mercilessly attacked those 104 keys. Machine learning is turning some of that around by replacing the typing with humans demonstrating the actions they want the robot to perform. Suddenly, a factory line-worker can be a robot trainer. This is not new, but a robot needs thousands of examples before it is ready to make an attempt. A new paper from researchers at the University of California, Berkeley, are adding the ability to infer so robots can perform after witnessing a task just one time.

A robotic arm with no learning capability can only be told to go to (X,Y,Z), pick up a thing, and drop it off at (X₂, Y₂, Z₂). Many readers have probably done precisely this in school or with a homemade arm. A learning robot generates those coordinates by observing repeated trials and then copies the trainer and saves the keystrokes. This new method can infer that when the trainer picks up a piece of fruit, and drops it in the red bowl, that the robot should make sure the fruit ends up in the red bowl, not just the location where the red bowl was before.

The ability to infer is built from many smaller lessons, like moving to a location, grasping, and releasing and those are trained with regular machine learning, but the inference is the glue that holds it all together. If this sounds like how we teach children or train workers, then you are probably thinking in the right direction.

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