Visualizing Magnetic Fields In 3D Space

[John] is working on his PhD in experimental earthquake physics, and with that comes all the trials of becoming a PhD; tuning students into the cool stuff in the field, and demonstrating tech created after 1970 to his advisers. One of the biggest advancements in his line of work in the last 30 or 40 years is all those sensors you can find in your cell phone. The three-axis magnetometer in your phone is easily capable of measuring the Earth’s magnetic field, and this chip only costs a few dollars. To demonstrate this, [John] built a 3D compass to show off the capability of these sensors, and have a pretty light show for the undergrads.

The magnetometer [John] is using is just a simple I2C magnetometer that can be found on Adafruit or Sparkfun. It’s not really anything special, but with a little bit of code, [John] can read the magnetic field strength in the x, y, and z axes.

Having a microcontroller spit out a bunch of numbers related to the local magnetic field just doesn’t seem fun, so [John] picked up two neopixel rings – one inside the other, and set 90 degrees out of plane with each other. This turns his magnetometer and Arduino setup into a real 3D compass. With this device, the local magnetic field can be visualized in the x, y, and z axes. It looks cool, which is great for undergrads, and it’s a great demonstration of what you can do with small, cheap electronic sensors.

[John] put up a screencast of a talk he gave at the American Geophysical Union meeting last year. You can check that out below.

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MagnID – Sneaky New Way of Interacting With Tablets

New magnetic tech dubbed “MagnID” is being presented this weekend at Stanford’s annual TEI conference. It is a clever hack aimed to hijack a tablet’s compass sensor and force it to recognize multiple objects. Here is a sneak peek at the possibilities of magnetic input for tablets.

Many tablets come with some sort of triaxial magnetic sensor but as [Andrea] and [Ian]’s demo shows, they are only capable of passing along the aggregate vector of all magnetic forces. If one had multiple magnetic objects, the sensor is not able to provide much useful information.

Their solution is a mix of software and hardware. Each object is given a magnet that rotates at a different known speed. This creates complex sinusoidal magnetic fields that can be mathematically isolated with bandpass filters. This also gives them distance to each object. The team added an Arduino with a magnetometer for reasons unexplained, perhaps the ones built into tablets are not sufficient?

The demo video below shows off what is under the hood and some new input mechanics for simple games, sketching, and a logo turtle. Their hope is that this opens the door to all manner of tangible devices.

Check out their demo at Standford’s 9th annual “Tangible, Embedded, Embodied Interaction” this January 15-19, 2015.

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A DIY Geomagnetic Observatory

Magnetometer observatory

[Dr. Fortin] teaches physics at a French High School, and to get his students interested in the natural world around them, he built a geomagnetic observatory, able to tell his students if they have a chance at seeing an aurora, or if a large truck just drove by.

We’ve seen this sort of device before, and the basic construction is extremely similar – a laser shines on a mirror attached to magnets. When a change occurs in the local magnetic field, the mirror rotates slightly and the laser beam is deflected. Older versions have used photoresistors, but [the doctor] is shining his laser on a piece of paper and logging everything with a webcam and a bit of OpenCV.

The design is a huge improvement over earlier DIY attempts at measuring the local magnetic field, if only because the baseline between the webcam and mirror are so long. When set up in his house, the magnetometer can detect cars parked in front of his building, but the data he’s collecting (French, but it’s just a bunch of graphs) is comparable to the official Russian magnetic field data.

DIY OLED Smart Watch

OLED DIY Smart Watch

What is better than making your own smart watch? Making one with an OLED display. This is exactly what [Jared] set out to do with his DIY OLED smart watch, which combines an impressive build with some pretty cool hardware.

When building a DIY smart watch, getting the hardware right is arguably the hardest part. After a few iterations, [Jared’s] OLED smart watch is all packaged up and looks great! The firmware for his watch can communicate with the PC via USB HID (requiring no drivers), contains a “watch face” for telling time, includes an integrated calendar, and support for an accelerometer. His post also includes all of the firmware and goes into some build details. With the recent popularity of smart watches and wearable electronics, we really love seeing functional DIY versions. This is just the beginning. In the future, [Jared] plans on adding Bluetooth Low Energy (BLE), a magnetometer, a smart sleep based alarm clock, and more! So be sure to look at his two older posts and keep an eye on this project as it unfolds. It is a very promising smart watch!

With Android L including support for smart watches (in the near future), it would be amazing to see DIY watches (such as this one) modified to run the new mobile OS. How great would it be to have an open hardware platform running such a powerful (open source-ish) OS? the possibilities are endless!

Measuring Magnetic Fields with a Robotic Arm


Learning how magnets and magnetic fields work is one thing, but actually being able to measure and see a magnetic field is another thing entirely! [Stanley’s] latest project uses a magnetometer attached to a robotic arm with 3 degrees of freedom to measure magnetic fields.

Using servos and aluminium mounting hardware purchased from eBay, [Stanley] build a simple robot arm. He then hooked an HMC5883L magnetometer to the robotic arm. [Stanley] used an Atmega32u4 and the LUFA USB library to interface with this sensor since it has a high data rate. For those of you unfamiliar with LUFA, it is a Lightweight USB Framework for AVRs (formerly known as MyUSB). The results were plotted in MATLAB (Octave is free MATLAB alternative), a very powerful mathematical based scripting language. The plots almost perfectly match the field patterns learned in introductory classes on magnetism. Be sure to watching the robot arm take the measurements in the video after the break, it is very cool!

[Stanley] has graciously provided both the AVR code and the MATLAB script for his project at the end of his write-up. It would be very cool to see what other sensors could be used in this fashion! What other natural phenomena would be interesting to map in three dimensions?

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Modeling an object with internal IMUs

[Joseph Malloch] sent in a really cool video of him modeling a piece of foam twisting and turning in 3D space.

To translate the twists, bends, and turns of his piece of foam, [Joseph] used several inertial measurement units (IMUs) to track the shape of a deformable object. These IMUs consist of a 3-axis accelerometer, 3-axis gyroscope, and a 3-axis magnetometer to track their movement in 3D space. When these IMUs are placed along a deformable object, the data can be downloaded from a computer and the object can be reconstructed in virtual space.

This project comes from the fruitful minds at the Input Devices and Music Interaction Lab at McGill University in Montreal. While we’re not quite sure how modeled deformable objects could be used in a user interface, what use is a newborn baby? If you’ve got an idea of what this could be used for, drop a note in the comments. Maybe the Power Glove needs an update – an IMU-enabled jumpsuit that would put the Kinect to shame.

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Advanced compass/accelerometer library for Arduino

We don’t have much personal experience with DOF hardware, but this Arduino library which reads and compensates for three-axis magnetometer and accelerometer data looks very impressive. It should work for existing hardware, but there’s also a demo design using a Honeywell HMC5883L compass and a Freescale MMA8453Q accelerometer which you can build yourself. Unfortunately these come in QFN packages (like most cheap accelerometers these days) so you may need to be creative when soldering.

What’s so special about this library? Watch the video after the break (use 720p in fullscreen to get the full effect) and you’ll see three different scatter plots of the output data. The image above is a capture of the third example, which is using the hard iron offset and accelerometer compensation. That is to say, metal on and around the board is accounted for, as well as the physical orientation of the device. Even if you have no prior experience with this type of hardware it’s easy to see the usefulness of this kind of software compensation.

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