Forget Artificial Intelligence; Think Artificial Life

If you are a science fiction fan, you are probably aware of one of the genre’s oddest dichotomies. A lot of science fiction is concerned about if a robot, alien, or whatever is a person. However — sometimes in the same story — finding life is as easy as asking the science officer with a fancy tricorder. If you go to Mars and meet Marvin, it is pretty clear he’s alive, but faced with a bunch of organic molecules, the task is a bit harder. Now it is going to get harder still because Cornell scientists have created a material that has an artificial metabolism and checks quite a few boxes of what we associate with life. You can read the entire paper if you want more detail.

Three of the things people look for to classify something as alive is that it has a metabolism, self-arranges, and reproduces. There are other characteristics, depending on who you ask, but those three are pretty crucial.

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FPGA Makes Digital Analog Computer

When you think of analog computing, it’s possible you don’t typically think of FPGAs. Sure, a few FPGAs will have specialized analog blocks, but usually they are digital devices. [Bruce Land] — a name well-known to Hackaday — has a post about building a digital differential analyzer using an FPGA and it is essentially an analog computer simulated on the digital fabric of an FPGA.

Whereas traditional analog computers use operational amplifiers to do mathematical integration, on the FPGA [Land] uses digital summers The devices simulate a system of differential equations, which can be nonlinear.

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This Machine Teaches Sign Language

Sign language can like any language be difficult to learn if you’re not immersed in it, or at least learning from someone who is fluent. It’s not easy to know when you’re making minor mistakes or missing nuances. It’s a medium with its own unique issues when learning, so if you want to learn and don’t have access to someone who knows the language you might want to reach for the next best thing: a machine that can teach you.

This project comes from three of [Bruce Land]’s senior electrical and computer engineering students, [Alicia], [Raul], and [Kerry], as part of their final design class at Cornell University. Someone who wishes to learn the sign language alphabet slips on a glove outfitted with position sensors for each finger. A computer inside the device shows each letter’s proper sign on a screen, and then checks the sensors from the glove to ensure that the hand is in the proper position. Two letters include making a gesture as well, and the device is able to track this by use of a gyroscope and compass to ensure that the letter has been properly signed. It appears to only cover the alphabet and not a wider vocabulary, but as a proof of concept it is very effective.

The students show that it is entirely possible to learn the alphabet reliably using the machine as a teaching tool. This type of technology could be useful for other applications as well, such as gesture recognition for a human interface device. If you want to see more of these interesting and well-referenced senior design builds we’ve featured quite a few, from polygraph machines to a sonar system for a bicycle.

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Using an FPGA to Navigate China’s Railroads

If you’re headed over to mainland China as a tourist, it’s possible to get to most of the country by rail. China is huge though, about the same size as the United States and more than twice the size of the European Union. Traveling that much area isn’t particularly easy. There are over 300 train terminals in China, and finding the quickest route somewhere is not obvious at all. This is an engineering challenge waiting to be solve, and luckily some of the students at Cornell Engineering have taken a stab at efficiently navigating China’s rail system using an FPGA.

The FPGA runs an algorithm for finding the shortest route between two points, called Dijkstra’s algorithm. With so many nodes this can get cumbersome for a computer to calculate, but the parallel processing of a dedicated FPGA speeds up the process significantly. The FPGA also includes something called a “hard processor system“, or HPS. This is not a soft-core, but dedicated computing hardware in the form of an ARM Cortex-A9. Testing showed that utilizing both the HPS and the FPGA can speed up the computation by up to ten times over a microcontroller alone.

This project goes into extreme detail on the methodology and the background of the math and coding involved, and is definitely worth a read if you’re interested in FPGAs or traveling salesman-esque problems. FPGAs aren’t the only dedicated hardware you can use to solve these kinds of problems though, if you have a big enough backpack while you’re traveling around China you could also use a different kind of computer.

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Building A Drone That (Almost) Follows You Home

There’s a great deal of research happening around the topic of autonomous vehicles of all creeds and colours. [Ryan] decided this was an interesting field, and took on an autonomous drone as his final project at Cornell University.

The main idea was to create a drone that could autonomously follow a target which provided GPS data for the drone to follow. [Ryan] planned to implement this by having a smartphone provide GPS coordinates to the drone over WiFi, allowing the drone to track the user.

As this was  a university project, he had to take a very carefully considered approach to the build. Given likely constraints on both money and time, he identified that the crux of the project was to develop the autonomous part of the drone, not the drone itself. Thus, off-the-shelf parts were selected to swiftly put together a drone platform that would serve as a test bed for his autonomous brain.

The write up is in-depth and shares all the gritty details of getting the various subsystems of the drone talking together. He also shares issues that were faced with altitude control – without any sensors to determine altitude, it wasn’t possible to keep the drone at a level height. This unfortunately complicated things and meant that he didn’t get to complete the drone’s following algorithm. Such roadblocks are highly common in time-limited university projects, though their educational value cannot be overstated. Overall, while the project may not have met its final goals, it was obviously an excellent learning experience, and one which has taught him plenty about working with drones and the related electronics.

For another take on autonomous flight, check out this high-speed AI racing drone.

Fully-functional Oscilloscope on a PIC

When troubleshooting circuits it’s handy to have an oscilloscope around, but often we aren’t in a lab setting with all of our fancy, expensive tools at our disposal. Luckily the price of some basic oscilloscopes has dropped considerably in the past several years, but if you want to roll out your own solution to the “portable oscilloscope” problem the electrical engineering students at Cornell produced an oscilloscope that only needs a few knobs, a PIC, and a small TV.

[Junpeng] and [Kevin] are taking their design class, and built this prototype to be inexpensive and portable while still maintaining a high sample rate and preserving all of the core functions of a traditional oscilloscope. The scope can function anywhere under 100 kHz, and outputs NTSC at 30 frames per second. The user can control the ground level, the voltage and time scales, and a trigger. The oscilloscope has one channel, but this could be expanded easily enough if it isn’t sufficient for a real field application.

All in all, this is a great demonstration of what you can accomplish with a microcontroller and (almost) an engineering degree. To that end, the students go into an incredible amount of detail about how the oscilloscope works since this is a design class. About twice a year we see a lot of these projects popping up, and it’s always interesting to see the new challenges facing students in these classes.

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An Education on SoC using Verilog

[Bruce Land] is one of those rare individuals who has his own Hackaday tag. He and his students at Cornell have produced many projects over the years that have appeared on these pages, lately with FPGA-related projects. If you only know [Land] from projects, you are missing out. He posts lectures from many of his classes and recently added a series of new lectures about developing with a DE1 System on Chip (SoC) using an Altera Cyclone FPGA using Verilog. You can catch the ten lectures on YouTube.

The class material is different for 2017, so the content is fresh and relevant. The DE1-SOC has a dual ARM processor and boots Linux from an SD card. There are several labs and quite a bit of background material. The first lab involves driving a VGA monitor. Another is a hardware solver for ordinary differential equations.

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