Hackaday Prize 2022: MasterPi Is A Capable Robot With Fancy Wheels

July 1, 2022 by Lewin Day 2 Comments

When it comes to building a mobile robot, often maneuverability is more important than outright speed. The MasterPi robot demonstrates this well, using fancy wheels to help it slide and skate in any direction needed.

Four DC gear-motors are fitted to a metal chassis, each one driving a mecanum wheel. These are special wheels with rollers fitted around their circumference at an angle that allows the robot to move in all directions and rotate in various ways depending on how each wheel is driven.

On top of this highly maneuverable chassis is placed a 5-degree-of-freedom robotic arm. The robot also gets a ultrasonic sensor for avoiding objects, as well as a camera for line-following duties. The camera also allows the robot to pick up blocks and identify their color, and it can then sort them into boxes. It’s all powered by a Raspberry Pi, running a bunch of Python code to make everything happen.

It’s a neat project that shows off just how capable a robot can be with some smart design choices and modern computing hardware on board. We’ve seen some other smart block sorters before, too. Continue reading “Hackaday Prize 2022: MasterPi Is A Capable Robot With Fancy Wheels” →

Talking Head Teaches Laplace Transform

August 9, 2020 by Al Williams 25 Comments

Most people who deal with electronics have heard of the Fourier transform. That mathematical process makes it possible for computers to analyze sound, video, and it also offers critical math insights for tasks ranging from pattern matching to frequency synthesis. The Laplace transform is less familiar, even though it is a generalization of the Fourier transform. [Steve Bruntun] has a good explanation of the math behind the Laplace transform in a recent video that you can see below.

There are many applications for the Laplace transform, including transforming types of differential equations. This comes up often in electronics where you have time-varying components like inductors and capacitors. Instead of having to solve a differential equation, you can perform a Laplace, solve using common algebra, and then do a reverse transform to get the right answer. This is similar to how logarithms can take a harder problem — multiplication — and change it into a simpler addition problem, but on a much larger scale.

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Dexter Robot Arm Embraces New Manufacturing With First Micro-Factory

March 9, 2020 by Mike Szczys 32 Comments

Haddington Dynamics, the company behind the Dexter robot arm that won the 2018 Hackaday Prize, has opened its first microfactory to build robot arms for Australia and Southeast Asia.

You may remember that the combination of Dexter’s makeup and capabilities are what let it stand out among robotics projects. The fully-articulated robot arm can be motion trained; it records how you move the arm and can play back with high precision rather than needing to be taught with code. The high-precision is thanks to a clever encoder makeup that leverages the power of FPGAs to amplify the granularity of its optical encodes. And it embraces advanced manufacturing to combine 3D printed and glue-up parts with mass produced gears, belts, bearings, and motors.

It’s a versatile robot arm, for a fraction of the cost of what came before it, with immense potential for customization. And did I mention that it’s open source? Continue reading “Dexter Robot Arm Embraces New Manufacturing With First Micro-Factory” →

Lego Machine Uses Machine Learning To Sort Itself Out

December 16, 2019 by Dan Maloney 8 Comments

In our opinion, the primary evidence of a properly lived childhood is an enormous box of every conceivable Lego piece, from simple bricks to girders and gears, all with a small town’s worth of minifigs swimming through it. It takes years of birthdays and Christmases to accumulate a Lego collection best measured by the pound, but like anything worth doing, it’s worth overdoing.

But what to do with such a collection? Digging through it to find Just the Right Piece™ can be frustrating, and bringing order to the chaos with manual sorting is just so impractical. How about putting some of those bricks to work with a machine-vision Lego sorter built from Lego?

[Daniel West]’s approach is hardly new – we’ve even featured brick-built Lego sorters before – but we’re impressed by its architecture. First, the mechanical system is amazing. It uses a series of conveyors to transport bricks from a hopper, winnowing the stream down as it goes. The final step is a vibratory feeder that places one piece on a conveyor at a time. Those pass under a camera attached to a Raspberry Pi, where OpenCV does background subtraction from the video stream, applies bounding boxes to the parts, and runs the images through a convolutional neural network (CNN) that’s been trained on a database of every Lego part. Servo-controlled gates then direct the parts into one of 18 bins. See it in action in the video below.

We must admit that we’re not sure what the sorting criteria are, as some bins seem nearly as chaotic as the input mix. Still, we appreciate the fine engineering, and award extra style points for all the Lego goodness.

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Why Ada Is The Language You Want To Be Programming Your Systems With

September 10, 2019 by Maya Posch 161 Comments

The Ada programming language was born in the mid-1970s, when the US Department of Defense (DoD) and the UK’s Ministry Of Defence sought to replace the hundreds of specialized programming languages used for the embedded computer systems that increasingly made up essential parts of military projects. Instead, Ada was designed to be be a single language, capable of running on all of those embedded systems, that offered the same or better level of performance and reliability.

With the 1995 revision, the language also targeted general purpose systems and added support for object-oriented programming (OOP) while not losing sight of the core values of reliability, maintainability and efficiency. Today, software written in Ada forms the backbone of not only military hardware, but also commercial projects like avionics and air-traffic control systems. Ada code controls rockets like the Ariane 4 and 5, many satellites, and countless other systems where small glitches can have major consequences.

Ada might also be the right choice for your next embedded project. Continue reading “Why Ada Is The Language You Want To Be Programming Your Systems With” →

Sorting LEGO Is Like Making A Box Of Chocolates

September 27, 2018 by Steven Dufresne 6 Comments

Did you know that chocolate candy production and sorting LEGO bricks have something in common? They both use the same techniques for turning clumps of chocolates or bricks into individual ones moving down a conveyor belt. At least that’s what [Paco Garcia] found out when making his LEGO Sorter.

However, he didn’t find that out right away. He first experimented with his own techniques, learning that if he fed bricks to his conveyor belt by dropping a batch of them in a line perpendicular to the direction of belt travel then no subsequent separation attempt of his worked. He then turned to [akiyuky’s] LEGO sorter for inspiration and dropped them onto the belt at an angle, ensuring that some bricks would be in front of others. A further trick he found is very well demonstrated in the chocolate sorting video below and shown in the image here. That is to use guides on the belt which serve to create speed differentials. Bricks move slower than the conveyor belt while pressed against a guide but when a brick leaves the guide, it accelerates to the speed of the conveyor belt, pulling away from the bricks still at the guide and thus separating them.

A further discovery had nothing to do with chocolate production, unless maybe for quality control. Once an individual brick had been separated out, it had to be classified. To do that he used Google’s Inception v3 neural network. But first, he had to retrain it for recognizing different types of LEGO bricks, something we’ve seen done before for use with recognizing playing cards. And to do the retraining, he needed many images of different bricks all separated into their different types. That’s where he came up with a clever trick. He used his own sorter for that. For example, to get a bunch of images of 1×1 bricks of different colors and orientations, he simply ran them through the sorter, saving the images to files and assigning them to the 1×1 brick class. He then used his desktop machine with a GeForce GT 730 GPU for the retraining, taking around 2.7 seconds per brick. For sorting though, he runs the trained neural network on a Raspberry Pi, taking 3.8 seconds for each brick. The resulting sorter works quite well, sorting with 89% accuracy. Watch it in action in the video below.
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LEGO: The Kristiansen Legocy

June 26, 2018 by Lauren Faris 75 Comments

Whether you are young, old, or a time traveling Vulcan, something unites all of us globally: the innocent LEGO blocks that encourage creativity over spoon-fed entertainment. Have you noticed the excess of zombified children and adults alike drooling over their collective screens lately? Back in the ancient times, all a child needed to create hours of joy were plastic interlocking bricks and a place for their parents to trip over them. The LEGO Group harbored the inspiration of our childhood inventiveness, and none of it would have been possible without the founder, Ole Kirk Kristiansen (or Christiansen). The humble carpenter from Denmark forever made his mark on the little Scandinavian country, one brick at a time.

Well, maybe not at first. You see the plastic LEGO bricks we all know and love were initially made of wood. And they were also not actually bricks.

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