Inverted Pendulum For The Control Enthusiast

Once you step into the world of controls, you quickly realize that controlling even simple systems isn’t as easy as applying voltage to a servo. Before you start working on your own bipedal robot or scratch-built drone, though, you might want to get some practice with this intricate field of engineering. A classic problem in this area is the inverted pendulum, and [Philip] has created a great model of this which helps illustrate the basics of controls, with some AI mixed in.

Called the ZIPY, the project is a “Cart Pole” design that uses a movable cart on a trolley to balance a pendulum above. The pendulum is attached at one point to the cart. By moving the cart back and forth, the pendulum can be kept in a vertical position. The control uses the OpenAI Gym toolkit which is a way to easily use reinforcement learning algorithms in your own projects. With some Python, some 3D printed parts, and the toolkit, [Philip] was able to get his project to successfully balance the pendulum on the cart.

Of course, the OpenAI Gym toolkit is useful for many more projects where you might want some sort of machine learning to help out. If you want to play around with machine learning without having to build anything, though, you can also explore it in your browser.

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Autonomous Agribots For Agriculture

For his Hackaday Prize entry, [TegwynTwmffat] is going all-in on autonomous robotics. No, it’s not a self-driving car with highly advanced features such as cruise control with lane-keeping. This is an autonomous robot that’s capable of driving itself. It’s a robot built for agriculture, and relative to other autonomous robotics projects, this one is huge. It’s the size of a small tractor.

The goal [Tegwyn]’s project is to build a robot capable of roving fields of crops to weed, harvest, and possibly fertilize the land. This is a superset of the autonomous car problem: not only does [Tegwyn] need to build a chassis to roll around a field, he needs accurate sensors, some sort of connection to the Internet, and a fast processor on board. The mechanical part of this build comes in the form of a rolling chassis that’s a bit bigger than a golf cart, and electrically powered (although there is a small Honda generator strapped to the back). The electronics is where this gets really interesting, with a rather large board built to house all the sensor and wireless modules, with everything controlled by a TC275, a multicore, 32-bit microcontroller that also has the world record for solving a Rubik’s cube.

Already, [Tegwyn] has a chassis and motor set up, and is already running some code to allow for autonomous navigation. It’s not much now — just rolling down a garden path — but then again, if you’re building a robot for agriculture, it’s not that hard to roll around an open field. You can check out a video of the bot in action below.

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The Solid State Weather Station

Building personal weather stations has become easier now than ever before, thanks to all the improvements in sensors, electronics, and prototyping techniques. The availability of cheap networking modules allows us to make sure these IoT devices can transmit their information to public databases, thereby providing local communities with relevant weather data about their immediate surroundings.

[Manolis Nikiforakis] is attempting to build the Weather Pyramid — a completely solid-state, maintenance free, energy and communications autonomous weather sensing device, designed for mass scale deployment. Typically, a weather station has sensors for measuring temperature, pressure, humidity, wind speed and rainfall. While most of these parameters can be measured using solid-state sensors, getting wind speed, wind direction and rainfall numbers usually require some form of electro-mechanical devices.

The construction of such sensors is tricky and non-trivial. When planning to deploy in large numbers, you also need to ensure they are low-cost, easy to install and don’t require frequent maintenance. Eliminating all of these problems could result in more reliable, low-cost weather stations to be built, which can then be installed in large numbers at remote locations.

[Manolis] has some ideas on how he can solve these problems. For wind speed and direction, he plans to obtain readings from the accelerometer, gyroscope, and compass in an inertial sensor (IMU), possibly the MPU-9150. The plan is to track the motion of the IMU sensor as it swings freely from a tether like a pendulum. He has done some paper-napkin calculations and he seems confident that it will provide the desired results when he tests his prototype. Rainfall measurement will be done via capacitive sensing, using either a dedicated sensor such as the MPR121 or the built-in touch capability in the ESP32. The design and arrangement of the electrode tracks will be important to measure the rainfall correctly by sensing the drops. The size, shape and weight distribution of the enclosure where the sensors will be installed is going to be critical too since it will impact the range, resolution, and accuracy of the instrument. [Manolis] is working on several design ideas that he intends to try out before deciding if the whole weather station will be inside the swinging enclosure, or just the sensors.

If you have any feedback to offer before he proceeds further, let him know via the comments below.

Flood Fault Circuit Interrupter Could Save Lives

What if you didn’t have to risk your life to disconnect the power during a catastrophic storm? That’s a question many people in Houston were asking themselves as they watched water from Hurricane Harvey and other storms surge through the streets, swell in the gutters, and flood their homes.

Among these Houstonians were engineering students [Jon] and [Cyrus Jyan]. They watched as homeowners fought to safely disconnect their homes from the power grid and said, it shouldn’t have to be this way. They designed the Flood Fault Circuit Interrupter to monitor target areas and disconnect the power automatically when a credible threat is detected.

The FFCI is built on top of existing protection schemes like GFCIs and Arc Fault Circuit Interrupters. It isn’t meant to replace them, but instead tie them together and turn them off based on input from float switches.

As floodwaters rise, an EEPROM does a lookup and compare to decide if the threat is enough to shut it down. If so, an alarm signal to a shunt trip breaker can either throw the whole system to OFF, or else switch over to an alternate power source. The system is built around a standard security panel and keypad interface that supports 12 V alarm output. We particularly like the float switch enclosures that allow water to enter while keeping out debris.

Reflowduino: Put That Toaster Oven To Good Use

There are few scenes in life more moving than the moment the solder paste melts as the component slides smoothly into place. We’re willing to bet the only reason you don’t have a reflow oven is the cost. Why wouldn’t you want one? Fortunately, the vastly cheaper DIY route has become a whole lot easier since the birth of the Reflowduino – an open source controller for reflow ovens.

This Hackaday Prize entry by [Timothy Woo] provides a super quick way to create your own reflow setup, using any cheap means of heating you have lying around. [Tim] uses a toaster oven he paid $21 for, but anything with a suitable thermal mass will do. The hardware of the Reflowduino is all open source and has been very well documented – both on the main page and over on the project’s GitHub.

The board itself is built around the ATMega32u4 and sports an integrated MAX31855 thermocouple interface (for the all-important PID control), LiPo battery charging, a buzzer for alerting you when input is needed, and Bluetooth. Why Bluetooth? An Android app has been developed for easy control of the Reflowduino, and will even graph the temperature profile.

When it comes to controlling the toaster oven/miscellaneous heat source, a “sidekick” board is available, with a solid state relay hooked up to a mains plug. This makes it a breeze to setup any mains appliance for Arduino control.

We actually covered the Reflowduino last year, but since then [Tim] has also created the Reflowduino32 – a backpack for the DOIT ESP32 dev board. There’s also an Indiegogo campaign now, and some new software as well.

If a toaster oven still doesn’t feel hacky enough for you, we’ve got reflowing with hair straighteners, and even car headlights.

MoAgriS: A Modular Agriculture System user [Prof. Fartsparkle] aims to impress us again with MoAgriS, a stripped-down rig for bringing crops indoors and providing them with all they need.

This project is an evolution of their submission to last year’s Hackaday Prize, MoRaLiS — a modular lighting system on rails — integrating modules for light, water, airflow, fertilizer and their appropriate sensors. With an emphasis on low-cost, a trio of metal bars serve as the structure, power and data transmission medium with SAM D11 chips shepherding each plant.

Reinforced, angled PCBs extend rails horizontally allowing the modules to be mounted at separate heights. Light module? Up top. Water sensor? Low on the rails above the pot’s rim. You get the idea. 3D printed clamps attach the rails to the plant’s pot with a touch of paint to keep it from sticking out like a sore thumb among the leaves.

Airflow modules replicate wind currents — the lack of which results in thin, fragile stems — and light modules include a soft white LED to accompany and mitigate the full-spectrum LEDs’ pink neon-like glow. To manage watering the plants, [Prof. Fartsparkle] initially wanted to use one pump to distribute water to every plant, but found some smaller pumps at a low enough price-point to make one per plant viable — and simpler to integrate as a module as well!

If you prefer your gardening to take place outdoors, consider a robot assistant to tackle your weeding.

Intra-Oral Device Detects Opioid Overdose

As you may have heard, the U.S. is in the grips of an opioid epidemic. Overdose deaths from heroin, oxycontin, and fentanyl have quadrupled since 1999. The key to detecting opioid overdose before it’s too late is in monitoring respiration. Opioids in particular cause depressed respiration, which is slow and ineffective breathing that’s inadequate for the gas exchange that keeps us alive. Depressed respiration becomes fatal unless the patient is given nalaxone, an antidote that works by blocking opioid receptors in the brain.

[Curt White] is developing an intra-oral device to prevent opioid overdose via early detection. It tracks a patient’s inhale/exhale rate and sends the data over Bluetooth to an open-source website.  The tiny device uses an air pressure sensor, a humidity sensor, and a thermopile thermometer to accurately track a person’s full respiration waveform whether their mouth is open or closed. The brain is one of [Curt]’s hacked $35 activity trackers that we told you about a few days ago.

All of the hardware including the battery is embedded in a custom retainer made from thermoplastic. [Curt] used Tyvek and surgical tape to isolate the air pressure sensor. Both are waterproof and breathable, which means that air can get to the sensor, but not saliva. Hold your breath and click past the break to watch [Curt] demonstrate this amazing tool on himself.

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