High-Tech Halloween

Still contemplating Halloween ideas? Do you have a costume yet? Is your house trick-or-treat ready? Perhaps some of these high-tech costumes and decorations will help get you in the spirit.

Recent Circuit Cellar interviewee Jeremy Blum designed a creative and high-tech costume that includes 12 individually addressable LEDs, an Adafruit microcontroller, and 3-D printing.

Skull_Side_Full_IMG_0067

Custom animatronic skull

RavenSide2Armature_IMG_0015

Animatronic talking raven

Looking for Halloween decoration inspiration? Peter Montgomery designed some programmable servo animation controllers built around a Freescale Semiconductor 68HC11 microcontroller and a Parallax SX28 configurable controller.

Peter’s Windows-based plastic skull is animated with RC servos controlled via a custom system. It moves at 24 or 30 frames per second over a custom RS-485 network.
This animatronic talking raven features a machined aluminum armature and moves via RC servos. The servos are controlled by a custom system using Windows and embedded controllers.

Peter’s Halloween projects were originally featured in “Servo Animation Controller” (Circuit Cellar 188, 2006). He displays the Halloween projects every year.

Feeling inspired? Share your tech-based Halloween projects with us.

MCU-Based Prosthetic Arm with Kinect

James Kim—a biomedical student at Ryerson University in Toronto, Canada—recently submitted an update on the status of an interesting prosthetic arm design project. The design features a Freescale 9S12 microcontroller and a Microsoft Kinect, which tracks arm movements that are then reproduced on the prosthetic arm.

He also submitted a block diagram.

Overview of the prosthetic arm system (Source: J. Kim)

Kim explains:

The 9S12 microcontroller board we use is Arduino form-factor compatible and was coded in C using Codewarrior.  The Kinect was coded in C# using Visual Studio using the latest version of Microsoft Kinect SDK 1.5.  In the article, I plan to discuss how the microcontroller was set up to do deterministic control of the motors (including the timer setup and the PID code used), how the control was implemented to compensate for gravitational effects on the arm, and how we interfaced the microcontroller to the PC.  This last part will involve a discussion of data logging as well as interfacing with the Kinect.

The Kinect tracks a user’s movement and the prosthetic arm replicates it. (Source: J. Kim, YouTube)

The system includes:

Circuit Cellar intends to publish an article about the project in an upcoming issue.

2012 ESC Boston: Tech from Microchip, Fujitsu, & More

The 2012 Embedded Systems Conference in Boston started September 17 and ends today. Here’s a wrap-up of the most interesting news and products.

MICROCHIP TECHNOLOGY

Microchip Technology announced Monday morning the addition of 15 new USB PIC microcontrollers to its line of full-speed USB 2.0 Device PIC MCUs. In a short presentation, Microchip product marketing manager Wayne Freeman introduced the three new 8-bit, crystal-free USB PIC families.

The PIC16F145x family (three devices) features the Microchip’s lowest-cost MCUs. The devices are available in 14- and 20-pin packages, support full-speed USB communication, don’t require external crystals, include PWM with complement generation, and more. They’re suitable for applications requiring USB connectivity and cap sense capabilities.

Microchip’s three PIC18F2x/4xK50 devices (available in 28- and 40/44-pins) enable “easy migration” from legacy PIC18 USB devices. In addition to 1.8- to 5-V operation, they feature a Charge Time Measurement Unit (CTMU) for cap-touch sensing, which makes them handy for data logging systems for tasks such as temperature and humidity measurement.

The nine devices in the PIC18F97J94 family are available in 64-, 80-, and 100-pin packages. Each device includes a 60 × 8 LCD controller and also integrates a real-time clock/calendar (RTCC) with battery back-up. Systems such as hand-held scanners and home automation panels are excellent candidates for these devices.

Several interesting designs were on display at the Microchip booth.

  • The M2M PICtail module was used in an SMS texting system.

This SMS text messaging system was featured at Microchip’s Machine-to-Machine (M2M) station. The M2M PICtail module (located on the bottom left) costs around $200.

  • Microchip featured its PIC MCU iPod Accessory Kit in glucose meter design. It was one of several healthcare-related systems that exhibitors displayed at the conference.

The interface can be an iPhone, iPad, or iPod Touch.

Visit www.microchip.com for more information.

RENESAS

As most of you know, the entry period for the Renesas RL78 Green Energy Challenge ended on August 31 and the judges are now reviewing the entries. Two particular demos on display at the Renesas booth caught my attention.

  • A lemon powering an RL78 L12 MCU:

Lemon power and the RL78

  • An R8C capacitive touch system:

Cap touch technology is on the minds of countless electrical engineers.

Go to www.am.renesas.com.

FREESCALE

I was pleased to see a reprint of Mark Pedley’s recent Circuit Cellar article, “eCompass” (August 2012), on display at Freescale’s booth. The article covers the topics of building and calibrating a tilt‐compensating electronic compass.

A Circuit Cellar reprint for attendees

Two of the more interesting projects were:

  • An Xtrinsic sensor demo:

Xtrinsic and e-compass

  • A Tower-based medical suitcase, which included a variety of boards: MED-BPM (a dev board for blood pressure monitor applications), MED-EKG (an aux board for EKG and heart rate monitoring applications), and more.

Tower System-based medical suitcase

STMicro

I stopped by the STMicro booth for a look at the STM32F3DISCOVERY kit, but I quickly became interested in the Dual Interface EEPROM station. It was the smartphone that caught my attention (again). Like other exhibitors, STMicro had a smartphone-related application on hand.

  • The Dual EEPROMs enable you to access memory via either  wired or RF interfaces. Energy harvesting is the new function STMicro is promoting. According to the documentation, “It also features an energy harvesting and RF status function.”

The Dual Interface EEPROM family has an RF and I2C interface

  • According to STMicro’s website, the DATALOG-M24LR-A PCB (the green board, top left) “features an M24LR64-R Dual Interface EEPROM IC connected to an STM8L101K3 8-bit microcontroller through an I2C bus on one side, and to a 20 mm x 40 mm 13.56 MHz etched RF antenna on the other one side. The STM8L101K3 is also interfaced with an STTS75 temperature sensor and a CR2330 coin cell battery.”

FUJITSU

I’m glad I spend a few moments at the Fujitsu booth. We rarely see Circuit Cellar authors using Fujitsu parts, so I wanted to see if there was something you’d find intriguing. Perhaps the following images will pique your interest in Fujitsu technologies.

The FM3 family, which features the ARM Cortext-M3 core, is worth checking out. FM3 connectivity demonstration

Connectivity demo

Check out Fujitsu’s System Memory site and document ion to see if its memory products and solutions suit your needs. Access speed comparison: FRAM vs. SRAM vs. EEPROM

Access speed comparison

The ESC conference site has details about the other exhibitors that had booths in the exhibition hall.

 

 

 

 

 

 

Implement a Tilt and Interference-Compensated Electronic Compass

Would you like to incorporate an electronic compass in a consumer product you’re designing or a personal device you’re constructing? If so, you’ll do well to understand as much as possible about the differences between various sensors and how certain forms of interference can affect their accuracies.

Mark Pedley of Freescale Semiconductor has an article in Circuit Cellar 265 (August 2012) on these topics. An abridged version of his article follows. Pedley writes:

 Whenever a new high-volume consumer electronics market develops, the semiconductor companies are never far behind, providing excellent components at surprisingly low prices. The market for sensors in consumer products is a recent example. It all started with an accelerometer used to select between portrait and landscape display orientations and then, with the addition of a magnetometer, evolved into the electronic compass (eCompass) used to align street maps to the smartphone’s geographic heading or to enable augmented reality overlays. As a result, high-volume pricing for smartphone accelerometer and magnetometer sensors is now less than $1 each.

A magnetometer sensor alone cannot provide an accurate compass heading for two reasons. First, the magnetic field measured at the magnetometer varies significantly with tilt angle. Second, the magnetometer requires calibrating not only for its own offset but also against spurious magnetic fields resulting from any nearby ferromagnetic components on the circuit board. This article describes how the accelerometer is used to compensate the magnetometer for tilt and includes a simple technique for calibrating the magnetometer.

SENSOR SELECTION

The accelerometer should be three axis and capable of operating in the ±2-g range with a minimum of 10 bits of resolution. The output of a 10-bit accelerometer operating in the ±2-g range will change by 512 counts as the accelerometer is rotated 180° from pointing downward to upward, giving an average sensitivity of one count per 0.35° change in tilt. This is more than adequate for tilt-compensation purposes.

It is important to check the accelerometer datasheet for the “0-g offset accuracy” which is the output when the accelerometer is in 0-g freefall. Since this value is a constant additive error on each accelerometer channel, it adds a bias in the calculated tilt angles, so look for accelerometers where this parameter does not exceed 50 mg.

The magnitude of the earth’s geomagnetic field is typically about 50 µT with a horizontal component that varies over the earth’s surface, from a maximum of about 40 µT down to 0 at the geomagnetic poles. If an eCompass is required to operate in horizontal geomagnetic fields down to 10 µT (in arctic Canada, for example) with a noise jitter of ±3°, then a back-of-the-envelope calculation indicates that a magnetometer with a maximum noise level of 0.5 µT is needed.

Most of my projects have used Freescale’s MMA8451Q Xtrinsic three-axis, 14-bit accelerometer and MAG3110 three-axis magnetometer. The MMA8451Q is supplied in a 3-mm × 3-mm × 1-mm, 16-pin QFN package and provides a 14-bit data output with ±30-mg, 0-g offset accuracy. The MAG3110 magnetometer is supplied in a 2-mm × 2-mm × 0.85 mm, 10-pin DFN package and provides a measurement range of ±1,000 µT with 0.1-µT resolution and a noise level down to 0.25 µT. Both parts operate with a supply voltage between 1.95 V and 3.6 V.

Similar sensors are supplied by Asahi Kasei (AKM), Kionix, STMicroelectronics, and other manufacturers. Your best strategy is to go to the manufacturers’ websites and make a list of those that provide samples in single units or low-volume packs of up to five devices. With a bit of luck, you may be able to get both the accelerometer and magnetometer sensors for free. Add a handful of decoupling capacitors and pull-up resistors and you should be well within the $5 component cost.

Each reader has a preferred microcontroller to read the raw data from the two sensors and implement the eCompass. This article assumes the microcontroller provides an I2C bus to interface to the sensors, supports floating-point operations whether natively or through software emulation libraries, and has a few spare bytes of program and data memory…

LAYOUT & BOARD BRING-UP

Once you’ve selected your sensors, the next step is to design the accelerometer and magnetometer daughterboard with I2C bus connection to the microcontroller. Reference schematics for the MMA8451Q and MAG3110 are provided in the sensor datasheets and reproduced in Figure 1.

Figure 1: Schematics for (a) MMA8451Q and (b) MAG3110 sensors (Source: M. Pedley, Circuit Cellar 265)

Don’t waste any time rotating the accelerometer or magnetometer packages to align their x-, y-, and z-sensing directions to each other since this will be  fixed later in software. But do ensure the sensor board will not be mounted in the immediate vicinity of any ferromagnetic materials since these will produce a constant additive magnetic field termed the “hard-iron field.” The most common ferromagnetic materials are iron, steel, ferrite, nickel, and cobalt. Non-ferromagnetic materials are all safe to use (e.g., aluminum, copper, brass, tin, silver, and gold).

The calibration process described later enables the estimation and software subtraction of any hard-iron field, but it’s good practice to minimize hard iron interference at the design stage. Remember, a current trace will create a cylindrical magnetic field that falls off relatively slowly with the inverse of distance, so place the magnetometer as far away from high current traces as possible. A 0.1-A current trace at 10-mm distance will produce a 2-µT magnetic field, four times our 0.5-µT error budget, only reducing to 0.5 µT at a 40-mm distance. More detailed layout guidance is provided in Freescale Semiconductor’s application note AN4247: “Layout Recommendations for PCBs Using a Magnetometer Sensor.”

You’ll be surprised at the number of features implemented in the latest consumer sensors (i.e., freefall detection, high- and low-pass filtering options, automatic portrait and landscape detection, etc.), but disable all these since you simply want the raw accelerometer and magnetometer data. Configure the accelerometer into a 2-g range and check that you can read the x, y, and z accelerometer and magnetometer data (in units of bit counts) from the sensors’ internal registers at a sampling rate of between 10 Hz and 50 Hz. Smartphones commonly use IDH3 to minimize power consumption while anything above 50 Hz is overkill. Check the accelerometer datasheet for the conversion factor between counts and g (4,096 counts per g for the MMA8451Q in ±2-g mode) and use this to scale the x, y, z accelerometer readings into units of g. Do the same for the x, y, z magnetometer data again taking the conversion factor from the magnetometer datasheet (10 counts per µT for the MAG3110).

COORDINATE SYSTEM

The equations and C software in Listing 1 use the “aerospace,” or “x-North y-East z-Down,” coordinate system depicted in Photo 1.

Listing 1: C source code for the tilt-compensated eCompass (Source: M. Pedley, Circuit Cellar 265)

This defines the initial eCompass orientation to be where the x-axis points north, the y-axis points east, and the z-axis points downwards. The three orientation angles, roll (ϕ), pitch (θ), and compass heading, or yaw (ψ)—are defined as clockwise rotations about the positive x, y, and z axes— respectively. Photo 1 also shows the earth’s gravitational vector which points downward with magnitude of 1 g or 9.81 ms-2 and the earth’s geomagnetic field vector, which points downward from horizontal (in the northern hemisphere) by the inclination angle δ to give a horizontal component B0cosδ and a downward component B0sinδ.

Photo 1: The aerospace noth-east-down coordinate system (Source: M. Pedley, Circuit Cellar 265)

Based on how your eCompass housing will be held, you should be able to assign the compass-pointing direction or x-axis, the downward or z-axis, and the y-axis, which should point to the right to complete a right-handed coordinate system.

AXIS ALIGNMENT & MAGNETIC CALIBRATION

You now need to align the sensor data to the aerospace coordinate system. As with all work with magnetometers, this should be performed on a wooden table well away from any laboratory power supplies or steel furniture. Place the eCompass flat and upright so the z-axis points downward and is aligned with gravity. Check that the accelerometer z-axis reads approximately 1 g and the x- and y-axes are near 0. Invert the eCompass so its z-axis points upward and check that the z-axis now reads approximately –1 g. Repeat with the x- and y-axes pointing downward and then upward and check that the x- and  y-axis accelerometer readings are near 1 g and –1 g, respectively. It’s not important if the accelerometer readings are a few tens of mg away from the required reading since all you’re doing here is correcting for gross rotations of the sensor packages and the sensor daughterboard in multiples of 90°. Any needed correction will be unique for your board layout and mounting orientation but will be no more complicated than “swap the x- and y-accelerometer channels and negate the z-channel reading.” Code this accelerometer axis mapping into your software and don’t touch it again.

Figure 2 may help explain this visually. The accelerometer sensor measures both gravity and linear acceleration and, in the absence of any linear acceleration (as is the case when sitting on a desk), the magnitude of the accelerometer reading will always equal 1 g, and therefore, lie on the surface of a 1-g sphere, irrespective of the orientation.

Figure 2: Accelerometer axis alignment points (Source: M. Pedley, Circuit Cellar 265)

The six measurements  lie on the vertices of an octahedron inscribed within the 1-g sphere and the axis mapping simply rotates and reflects the octahedron as needed until the accelerometer channels are correctly aligned.

The magnetometer axis alignment is similar to that of the accelerometer, but makes use of the geomagnetic field vector. Place the eCompass flat, upright, and pointing northward and then rotate in yaw angle by 270° to the east, south, and finally west. The x-channel magnetometer reading should be a maximum when the eCompass is pointed north and a minimum when pointed south. The y-channel magnetometer reading should be a minimum when the eCompass is pointed east and a maximum when pointed west. The z-channel reading should be approximately constant since the vertical component of the geomagnetic field is constant irrespective of rotation in yaw.

Then invert the eCompass on the desk and repeat the process. As before, the magnetometer x-axis reading should be a maximum when the eCompass is pointed north and a minimum when pointed south. But now, because of the inverted position, the magnetometer y-axis should be a maximum when the eCompass is pointed east and a minimum when pointed west. The magnetometer z-axis reading should still be constant but, in the northern hemisphere, lower than the previous upright readings since the magnetometer z-axis is now aligned against the downward component of the geomagnetic field vector.

Figure 3 shows upright and inverted magnetometer measurements taken in the northern hemisphere with a 270o compass rotation.

Figure 3: The upright (a) and inverted (b) magnetometer measurements (Source: M. Pedley, Circuit Cellar 265)

The maximum and minimum of the x- and y-axis magnetometer measurements occur at the expected angles and the z-axis measurement is less when inverted than when upright. These magnetometer axes are therefore correctly aligned but, as with the accelerometer correction, swap and negate the measurements from your three magnetometer channels as needed until correctly aligned and then lock down this part of your code.

A lot can be learned by closely looking at the measurements in Figure 3. The x- and y-magnetometer measurements lie on a circle with radius of approximately 25 µT enabling us to deduce that the horizontal geomagnetic field is approximately 25 µT. But the measurements are offset from zero by the magnetic “hard iron” interfering field, which results from both permanently magnetized ferromagnetic materials on the circuit board and from a zero-field offset in the magnetometer sensor itself. Consumer sensor manufacturers long ago realized it was pointless to accurately calibrate their magnetometers when their target market is smartphones, each with a different hard-iron interfering field. The magnetometer sensor offset is, therefore, calibrated together with the circuit board hard-iron magnetic field. For now, simply note that the x and y components of the hard iron offset have values of approximately 215 µT and 185 µT. A simple method to determine all three hard-iron components is described later.

Refer to the complete article for information about calculating the roll and pitch angles and determining the compass heading angle.

Mark Pedley has a Physics degree from Oxford University and now works on sensor fusion algorithms for Freescale Semiconductor in Tempe, Arizona.

Issue 265: Embedded Systems Abound

I recently read on CNN.com the transcript of an interview (May 9, 2002) with arachnologist Norman Platnick who stated: “You’re probably within seven or eight feet of spider no matter where you are. The only place on earth that has no spiders at all—as far as we know—is Antarctica.” It didn’t take long for me to start thinking about embedded systems and my proximity to them. Is the average person always within several feet of embedded systems? Probably not. But what about 50% or 60% of the time? E-mail me your thoughts.

Circuit Cellar 265, August 2012 - Embedded Development

Embedded systems are becoming ubiquitous. They’re in vehicles, mobile electronics, toys, industrial applications, home appliances, and more. If you’re indoors, the temperature is likely monitored and controlled by an embedded system. When you’re engaged in outdoor activities (e.g., hiking, golfing, biking, or boating), you probably have a few MCU-controlled devices nearby, such as cell phones, rangefinders, pedometers, and navigation systems. This month we present articles about how embedded systems work, and our authors also provide valuable insight about topics ranging from concurrency to project development.

Freescale’s Mark Pedley kicks off the issue with a revealing article about a tilt-compensating electronic compass (p. 16). Now you can add an e-compass to your next MCU-based project.

E-compass technology (Source: M. Pedley, CC265)

Turn to page 24 for an in-depth interview with Italy-based engineer Guido Ottaviani. His fascination with electronics engineering, and robotics in particular, will inspire you.

Have you ever come across a product that you know you could have designed better? Scott Weber had that experience and then acted on his impulse to build a more effective system. He created an MCU-based light controller (p. 32).

The MCU-based light controller is on the right (Source: S. Weber, CC265)

If you want to ensure a microcontroller works efficiently within one of your systems, you should get to know it inside and out. Shlomo Engelberg examines the internal structure of an I/O pin with a pull-up resistor (p. 40).

Bob Japenga continues his series “Concurrency in Embedded Systems” on page 44. He covers atomicity and time of check to time of use (TOCTTOU).

On page 48 George Novacek presents the second part of his series on project development. He covers project milestones and design reviews.

Ed Nisley’s June 2012 article introduced the topic of MOSFET channel resistance. On page 52 he covers his Arduino-based MOSFET tester circuitry and provides test results.

The MOSFET tester PCB hides the Arduino that runs the control program and communicates through the USB cable on the left edge. (Source: E. Nisley, CC265)

If you read Robert Lacoste’s June 2012 article, you now understand the basics of frequency mixers. This month he presents high-level design methods and tools (p. 58).

Jeff Bachiochi wraps up the issue with an examination of a popular topic—energy harvesting (p. 68). He covers PV cell technology, maximum power point tracking (MPPT), and charge management control.

A great way to investigate MPPT for your design is to use an STMicroelectronics evaluation board, such as this STEVAL-ISV006V2 shown in the top of the photo. The smaller cell in the center is rated at 165 mW (0.55-V output at 0.3 A) measuring 1.5” × 0.75”. At the bottom is a Parallax commercial-quality solar cell that is rated at 2.65 W (0.534-V output at 5.34 A) measuring 125 mm. (Source: J. Bachiochi, CC265)

Circuit Cellar 265 is currently on newsstands.