Pick-And-Place Machine For Candy

Every December and May the senior design projects from engineering schools start to roll in. Since the students aren’t yet encumbered with real-world detractors (like management) the projects are often exceptional, unique, and solve problems we never even thought we had. Such is the case with [Mark] and [Peter]’s senior design project: a pick and place machine that promises to solve all of life’s problems.

Of course we’ve seen pick-and-place machines before, but this one is different. Rather than identifying resistors and capacitors to set on a PCB, this machine is able to identify and sort candies. The robot — a version of the MeARM — has three degrees of freedom and a computer vision system to alert the arm as to what it’s picking up and where it should place it. A Raspberry Pi handles the computer vision and feeds data to a PIC32 which interfaces with the hardware.

One of the requirements for the senior design class was to keep the budget under $100, which they were able to accomplish using pre-built solutions wherever possible. Robot arms with dependable precision can’t even come close to that price restraint. But this project overcomes the lack of precision in the MeArm by using incremental correcting steps to reach proper alignment. This is covered in the video demo below.

Senior design classes are a great way to teach students how to integrate all of their knowledge into a final class, and the professors often include limits they might find in the real world (like the budget limit in this project). The requirement to thoroughly document the build process is also a lesson that more people could stand to learn. Senior design classes have attempted to solve a lot of life’s other problems, too; from autonomous vehicles to bartenders, there’s been a solution for almost every problem.

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Softer Side Of Robots Is Future Of Space

What will next generation space suits look like? Kari Love is making the case that new space suits will exhibit the best in soft robot technology. The problem is that most people don’t really understand much about soft robots, or about space for that matter. Her talk at the Hackaday SuperConference explores the research she has been doing into future generations of space suits. Check out the video below and then join us after the break for more on this topic.

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“What Is My Purpose?” You Amplify And Display Signals.

[Andy_Fuentes22] likes to stream music, but is (understandably) underwhelmed by the sound that comes out of his phone. He wanted to build something that not only looks good, but sounds good. Something that could stream music through a Chromecast or a Raspi, but also take auxiliary input. Something awesome, like the Junkbots Sound System.

The ‘bots, named LR-E (Larry) and R8-CHL (Rachel), aren’t just cool pieces of art. They’re both dead-bug-walking bots with an LM386-based amplifier circuit and an AN6884-based VU meter in their transparent, industrial relay bodies. LR-E is the left channel, and his lovely wife is the right channel. The best part is that they are wired into the circuit through their 3.5mm plug legs and the corresponding jacks mounted in the Altoids tin base.

[Andy] built this labor of love from the ground up. He started with some very nice design sketches and took a bazillion pictures along the way. We think it sounds pretty good, but you can judge for yourself after the break. If VU meters are your jam, here’s another that’s built into the speaker.

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[Fran Blanche] Goes In-Depth With The Maillardet Automaton

We’re not specialists, but the Maillardet Automaton is one of the more amazing mechanical machines that we’ve seen in a while, and [Fran Blanche] got to spend some time with it in an attempt to figure out how it’s mysterious missing pen apparatus would have worked. The resulting video, embedded below, is partially her narrative about the experiment she’s running, and part straight-up mechanical marvel.

If you need a refresher course on Maillardet’s Automaton, we’ll send you first to Wikipedia, and then off to watch this other video , which has a few great close-ups of the cams that drive everything.

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Use Machine Learning To Identify Superheroes And Other Miscellany

[Massimiliano Patacchiola] writes this handy guide on using a histogram intersection algorithm to identify different objects. In this case, lego superheroes. All you need to follow along are eyes, Python, a computer, and a bit of machine learning magic.

He gives a good introduction to the idea. You take a histogram of the colors in a properly cropped and filtered photo of the object you want to identify. You then feed that into a neural network and train it to identify the different superheroes by color. When you feed it a new image later, it will compare the new image’s histogram to its model and output confidences as to which set it belongs.

This is a useful thing to know. While a lot of vision algorithms try to make geometric assertions about the things they see, adding color to the mix can certainly help your friendly robot project recognize friend from foe.

 

TastingFeet: Building Toes And Tongues

Noodle Feet is a robot — an artistically designed robot — that is a character from Sarah Petkus’ webcomic Gravity Road. This webcomic explores a post-human universe inhabited by robots, and dives deep into these robots’ exploration of the trash left behind from a human civilization.

Sarah’s not just drawing these robots. She’s bringing them to life. The character Noodle Feet, so named because his legs are encased in pool noodles, has been made real with an aluminum skeleton, a PCB brain, and infrared detecting eyes. At the 2016 Hackaday SuperConference Sarah gave a talk on the challenges of making this robot real and the specifics of making her robot dig its toes into carpet, slobber all over the floor, and taste with its artificial tongue.

Since last year’s talk on Noodle Feet, Sarah has vastly improved the gripping strength of her noodle’s feet. Over the last two years of construction the mechanism to extend grippy, cat-like toenails has moved from cheap hobby servos to solenoids to a clever cam system. While these toe feet worked, the grip was never quite right, and the world isn’t completely covered in shag carpet. After the break we’ll take a closer look at the improvements that Sarah made to the design and how she came up with the ideas for each new iteration.

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Train Your Robot To Walk With A Neural Network

[Basti] was playing around with Artificial Neural Networks (ANNs), and decided that a lot of the “hello world” type programs just weren’t zingy enough to instill his love for the networks in others. So he juiced it up a little bit by applying a reasonably simple ANN to teach a four-legged robot to walk (in German, translated here).

While we think it’s awesome that postal systems the world over have been machine sorting mail based on similar algorithms for years now, watching a squirming quartet of servos come to forward-moving consensus is more viscerally inspiring. Job well done! Check out the video embedded below.

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