The Basics of Thermocouples

Whether you’re looking to build a temperature-sensing device or you need to add sensing capabilities to a larger system, you should familiarize yourself with thermocouples and understand how to design thermocouple interfaces. Bob Perrin covered these topics and more in 1999 Circuit Cellar Online article , “The Basics of Thermocouples.” The article appears below in its entirety.

A mathematician, a physicist, and an engineer were at lunch. The bartender asked the three gentlemen, “what is this pi I hear so much about?”

The mathematician replied, “pi is the ratio of a circle’s circumference to its diameter.”

The physicist answered, “pi is 3.14159265359.”

The engineer looked up, flatly stated, “Oh, pi’s about three,” then promptly went back to doodling on the back of his napkin.

The point is not that engineers are sloppy, careless, or socially inept. The point is that we are eminently practical. We are solvers of problems in a non-ideal world. This means we must be able to apply concepts to real problems and know when certain effects are negligible in our application.

For example, when designing first- or second-order filters, 3 is often a close enough approximation for pi, given the tolerance and temperature dependence of affordable components.

But, before we can run off and make gross approximations, we must understand the physical principles involved in the system we’re designing. One topic that seems to suffer from gross approximations without a firm understanding of the issues involved is temperature measurement with thermocouples.

Thermocouples are simple temperature sensors consisting of two wires made from dissimilar alloys. These devices are simple in construction and easy to use. But, like any electronic component, they require a certain amount of explanation. The intent of this paper is to present and explain how to use thermocouples and how to design thermocouple interfaces.


Figure 1a shows a thermocouple. One junction is designated the hot junction. The other junction is designated as the cold or reference junction. The current developed in the loop is proportional to the difference in temperature between the hot and cold junctions. Thermocouples measure differences in temperature, not absolute temperature.

Figure 1a: Two wires are all that are required to form a thermocouple.

To understand why a current is formed, we must revert to physics. Unfortunately, I’m not a physicist, so this explanation may bend a concept or two, but I’ll proceed nonetheless.

Consider a homogenous metallic wire. If heat is applied at one end, the electrons at that end become more energetic. They absorb energy and move out of their normal energy states and into higher ones. Some will be liberated from their atoms entirely. These newly freed highly energetic electrons move toward the cool end of the wire. As these electrons speed down the wire, they transfer their energy to other atoms. This is how energy (heat) is transferred from the hot end to the cool end of the wire.

As these electrons build up at the cool end of the wire, they experience an electrostatic repulsion. The not-so-energetic electrons at the cool end move toward the hot end of the wire, which is how charge neutrality is maintained in the conductor.

The electrons moving from the cold end toward the hot end move slower than the energetic electrons moving from the hot end move toward the cool end. But, on a macroscopic level, a charge balance is maintained.

When two dissimilar metals are used to form a thermocouple loop, as in Figure 1a, the difference in the two metal’s affinity for electrons enables a current to develop when a temperature differential is set up between the two junctions.

As electrons move from the cold junction to the hot junction, these not-so-energetic electrons are able to move easier in one metal than the other. The electrons that are moving from the hot end to the cold end have already absorbed a lot of energy, and are free to move almost equally well in both wires. This is why an electric current is developed in the loop.

I may have missed some finer points of the physics, but I think I hit the highlights. If anyone can offer a more in-depth or detailed explanation, please e-mail me. One of the best things about writing for a technical audience is learning from my readers.


If you use thermocouples, you must insert a measurement device in the loop to acquire information about the temperature difference between the hot and cold junctions. Figure 1b shows a typical setup. The thermocouple wires are brought to a terminal block and an electric circuit measures the open circuit voltage.

Figure 1b: To use a thermocouple, you must have a measurement system.

When the thermocouple wires are connected to the terminal block, an additional pair of thermocouples is formed (one at each screw terminal). This is true if the screw-terminals are a different alloy from the thermocouple wires. Figure 1c shows an alternate representation of Figure 1b. Junction 2 and junction 3 are undesired artifacts of the connection to the measurement circuitry. These two junctions are commonly called parasitic thermocouples.

Figure 1c: The act of connecting a measurement system made of copper introduces two parasitic thermocouples.

In a physical circuit, parasitic thermocouples are formed at every solder joint, connector, and even every internal IC bond wire. If it weren’t for something called the Law of Intermediate Metals, these parasitic junctions would cause us endless trouble.

The Law of Intermediate Metals states that a third metal may be inserted into a thermocouple system without affecting the system if, and only if, the junctions with the third metal are kept isothermal (at the same temperature).

In Figure 1c, if junction 2 and junction 3 are at the same temperature, they will have no effect on the current in the loop. The voltage seen by the voltmeter in Figure 1b will be proportional to the difference in temperature between Junction 1 and Junctions 2 and 3.

Junction 1 is the hot junction. The isothermal terminal block is effectively removed electrically from the circuit, so the temperature of the cold junction is the temperature of the terminal block.


Thermocouples produce a voltage (or loop current) that is proportional to the difference in temperature between the hot junction and the reference junction. If you want to know the absolute temperature at the hot junction, you must know the absolute temperature of the reference junction.

There are three ways to find out the temperature of the reference junction. The simplest method is to measure the temperature at the reference junction with a thermistor or semiconductor temperature sensor such as Analog Devices’ TMP03/04. Then, in software, add the measured thermocouple temperature (the difference between the hot junction and the reference junction) to the measured temperature of the reference junction. This calculation will yield the absolute temperature of the hot junction.

The second method involves holding the reference junction at a fixed and known temperature. An ice bath, or an ice slushy, is one of the most common methods used in laboratory settings. Figure 2 shows how this is accomplished.

Figure 2: By inserting a short pigtail of Metal A onto the terminal block where Metal B would normally connect, we move the cold junction.

Alternately, we could have omitted the pigtail of Metal A and just immersed the terminal block in the ice. This would work fine, but it would be much messier than the method shown in Figure 2.

Sometimes, the temperature of the cold junction (terminal block) in Figure 1c is allowed to float to ambient. Then ambient is assumed to be “about 25°C,” or some other “close enough” temperature. This method is usually found in systems where knowing the temperature of the hot junction is not overly critical.

The third method used to nail down the cold junction temperature is to use a cold junction compensation IC such as the Analog Devices AD594 or Linear Technology LT1025. This method sort of combines the first two methods.

These ICs have a temperature sensor in them that detects the temperature of the cold junction. This is presumably the same temperature as the circuit board on which the IC is mounted. The IC then produces a voltage that is proportional to the voltage produced by a thermocouple with its hot junction at ambient and its cold junction at 0°C. This voltage is added to the EMF produced by the thermocouple. The net effect is the same as if the cold junction were physically held at 0°C.

The act of knowing (or approximating) the cold junction temperature and taking this information in to account in the overall measurement is referred to as cold junction compensation. The three techniques I discussed are each methods of cold junction compensation.

The ice bath is probably the most accurate method. An ice slushy can maintain a uniformity of about 0.1°C without much difficulty. I’ve read that an ice bath can maintain a uniformity of 0.01°C, but I’ve never been able to achieve that level of uniformity. Ice baths are physically awkward and therefore usually impractical for industrial measurements.

The off-the-shelf cold junction compensation ICs can be expensive and generally are only accurate to a few degrees Celsius, but many systems use these devices.

Using a thermistor, or even the PN junction on a diode or BJT, to measure the cold junction temperature can be fairly inexpensive and quite accurate. The most common difficulty encountered with this system is calibration. Prudent positioning of the sensor near, or on the terminal block is important.

If the terminal block is to be used as the cold junction (see Figure 1b), the terminal block must be kept isothermal. In practice, keeping the terminal block truly isothermal is almost impossible. So, compromises must be made. This is the stock and trade of engineers. Knowing what is isothermal “enough” for your application is the trick.

Lots of money can be wasted on precision electronics if the terminal block’s screw terminals are allowed to develop a significant thermal gradient. This condition generally happens when power components are placed near the terminal blocks. You must pay careful attention to keeping the temperature stable around the terminal blocks.

There are two broad classes of temperature-measurement applications. The first class involves measuring absolute temperature. For example, you may want to know the temperature of the inside of an oven relative to a standard temperature scale (like the Celsius scale). This type of application requires that you know precisely the absolute temperature of the reference junction.

The second type of measurement involves measuring differences in temperature. For example, in a microcalorimeter, you may want to measure the temperature of the system, then start some chemical reaction and measure the temperature as the reaction proceeds. The information of value is the difference between first measurement and the subsequent ones.

Systems that measure temperature differences are generally easier to construct because control or precise measurement of the reference junction isn’t required. What is required is that the reference junction remain at a constant temperature while the two measurements occur. Whether the reference junction is at 25.0°C or 30.0°C isn’t relevant because the subtraction of consecutive measurements will remove the reference junction temperature from the computed answer.

You can use thermocouples to make precise differential temperature measurements, but you must ensure the terminal block forming the cold junction is “close enough” to isothermal. You must also ensure that the cold junction has enough thermal mass so it will not change temperature over the time you have between measurements.


Thermocouples are given a letter designation that indicates the materials they are fabricated from. This letter designation is called the thermocouples “type.” Table 1 shows the common thermocouples available and their usable temperature ranges.

Table 1: There are a wide variety of industry-standard alloy combinations that form standard thermocouples. The most commonly used are J, K, T, and E.

Each thermocouple type will produce a different open-circuit voltage (Seebeck voltage) for a given set of temperature conditions. None of these devices are linear over a full range of temperatures. There are standard tables available that tabulate Seebeck voltages as a function of temperature.[1] There are also standard polynomial models available for thermocouples.

Thermocouples produce a small Seebeck voltage. For example, a type K thermocouple produces about 40 µV per degree Celsius when both junctions are near room temperature. The most sensitive of the thermocouples, type E, produces about 60 µV per degree Celsius when both junctions are near room temperature.

In many applications, the range of temperatures being measured is sufficiently small that the Seebeck voltage is assumed to be linear over the range of interest. This eliminates the need for lookup tables or polynomial computation in the system. Often the loss of absolute accuracy is negligible, but this tradeoff is one the design engineer must weigh carefully.


When designing a thermocouple interface, there are only a few pieces of information you need to know:

  • what type of thermocouple will be used
  • what is the full range of temperatures the hot junction will be exposed to
  • what is the full range of temperatures the cold junction will be exposed to
  • what is the temperature resolution required for your application
  • does your system require galvanic isolation
  • what type of cold junction compensation will be used

If the answer to the last question requires the analog addition of a voltage from a commercial cold junction compensation IC, then the manufacturer of the IC will probably supply you with an adequate reference design. If you plan to do the cold-junction compensation either physically (by an ice bath) or in software (by measuring the cold junction’s temperature with another device), then you must build or buy a data-acquisition system.

Galvanic isolation is an important feature in many industrial applications. Because thermocouples are really just long loops of wire, they will often pick up high levels of common-mode noise. In some applications, the thermocouples may be bonded to equipment that is at line voltage (or higher).

In this case, galvanic isolation is required to keep high-voltage AC out of your data acquisition system. This type of isolation is usually accomplished in one of two ways—using either an opto-isolator or a transformer. Both systems require the thermocouple signal conditioner to allow its ground to float with respect to earth ground. Figure 3a and 3b outlines these schemes.

Figure 3: Galvanic isolation to a few thousand volts is easy (but a little expensive) using opto-isolation (a) and inexpensive (but a bit more challenging) using a VFC and a transformer (b).

Because the focus of this article is on the interface to the thermocouple, I’ll have to leave the details of implementing galvanic isolation to another article.

Given the tiny voltage levels produced by a thermocouple, the designer of the signal-conditioning module should focus carefully on noise rejection. Using the common-mode rejection (CMR) characteristics of a differential amplifier is a good place to start. Figure 4 shows a simple yet effective thermocouple interface

Figure 4: The common-mode filter and common-mode rejection characteristics pay off in thermocouple amplifiers.

The monolithic instrumentation amplifier (in-amp) is a $2–$5 part (depending on grade and manufacturer). These are usually 8-pin DIP or SOIC devices. In-amps are simple differential amplifiers. The gain is set with a single external resistor. The input impedance of an in-amp is typically 10 gigaohms.

Certainly you can use op-amps, or even discrete parts to build a signal conditioner. However, all the active components on a monolithic in-amp are on the same dice and are kept more-or-less isothermal. This means in-amp characteristics behave nicely over temperature. Good CMR, controllable gain, small size, and high input impedance make in-amps perfect as the heart of a thermocouple conditioning circuit.

Temperature tends to change relatively slowly. So, if you find your system has noise, you can usually install supplementary low-pass filters. These can be implemented in hardware or software. In many systems, it’s not uncommon to take 128 measurements over 1 s and then average the results. Digital filters are big cost reducers in production systems.

Another problem often faced when designing thermocouple circuits is nulling amplifier offset. You can null the amplifier offset in a variety of ways [2], but my favorite is by chopping the input. Figure 5 shows how this process can be accomplished.

Figure 5: An input chopper like a CD4052 is all that is necessary to null signal conditioner offsets.

Thermocouples have such small signal levels, gains on the order of 1000 V/V are not uncommon, which means an op-amp or in-amp with a voltage offset of even 1 mV will have an offset at the output on the order of volts.

The chopper in Figure 5 allows the microcontroller to reverse the polarity of the thermocouple. To null the circuit, the microcontroller will take two measurements then subtract them.

First, set the chopper so the ADC measures GAIN (Vsensor + Voffset). Second, set the chopper so the ADC measures GAIN (–Vsensor + Voffset).

Subtract the second measurement from the first and divide by two. The result is GAIN*Vsensor. As you can see, this is exactly the quantity we are interested in. The in-amp’s offset has been removed from the measurement.


In 1821, Thomas J. Seebeck discovered that if a junction of two dissimilar metals is heated, a voltage is produced. This voltage has since been dubbed the Seebeck voltage.

Thermocouples are found in everything from industrial furnaces to medical devices. At first glance, thermocouples may seem fraught with mystery. They are not. After all, how can a device that’s built from two wires and has been around for 180 years be all that tough to figure out?

When designing with thermocouples, just keep these four concepts in mind and the project will go much smoother. First, thermocouples produce a voltage that is proportional to the difference in temperature between the hot junction and the reference junction.

Second, because thermocouples measure relative temperature differences, cold junction compensation is required if the system is to report absolute temperatures. Cold-junction compensation simply means knowing the absolute temperature of the cold junction and adjusting the reparted temperature value accordingly.

The third thing to remember is that thermocouples have a small Seebeck voltage coefficient, typically on the order of tens of microvolts per degree Celsius. And last, thermocouples are non-linear across their temperature range. Linearization, if needed, is best done in software.

Armed with these concepts, the circuits in this article, and a bit of time, you should have a good start on being able to design a thermocouple into your next project.

Bob Perrin has designed instrumentation for agronomy, soil physics, and water activity research. He has also designed embedded controllers for a variety of other applications.



[2] B.Perrin, “Practical Analog Design,” Circuit Cellar, #94, May 1998.


AD594, TMP03/04
Analog Devices

Texas Instruments (Burr-Brown Corp.)

Linear Technology

This article was originally published in Circuit Cellar Online in 1999. Posted with permission. Circuit Cellar and are Elektor International Media publications.


In Memoriam: Richard Alan Wotiz

Richard Alan Wotiz—a multitalented electronics engineer, inventor, and author—provided the international embedded design community with creative projects and useful electronics engineering lessons since the early 1980s when he graduated from Princeton University. Sadly, Richard passed away unexpectedly on May 30, 2012 while hiking with a group of friends (a group called “Take a Hike”) in Santa Cruz County, California.

Richard Alan Wotiz

Richard started writing his “Embedded Unveiled” column for Circuit Cellar magazine in 2011. You can read each of his columns by clicking the links below:

Prior to becoming a columnist, Richard placed highly in several international embedded design challenges. Amazingly, he won First Prize in both the Texas Instruments 2010 DesignStellaris Challenge and the 2010 WIZnet iMCU Challenge. That’s right—he won First Place in both of Circuit Cellar’s 2010 design challenges!

Richard published intriguing feature article about some of his prize-winning projects. Interestingly, he liked combining his passion for engineering with his love of the outdoors. When he did so, the results were memorable designs intended to be used outdoors: a backpack water level monitor, an earth field magnetometer, and an ABS brake system for a mountain bike.

Richard’s ABS system is built around a Texas Instruments EKK-LM3S9B96 evaluation board, which contains the Stellaris LM3S9B96 microcontroller and support circuitry. The mechanism mounts to the front fork in place of the reflector, and the control unit sits on a bracket that’s also attached to the handlebars. A veritable maze of wires runs to the various sensors on the brake levers and wheels.

His other projects were well-built systems—such as his single-phase, variable-speed drive for AC induction motors—intended to solve real-world problems or handy DIY designs—such as his “Net Butler” network control system—that he could use in his daily life.

Richard’s single-phase, variable-speed drive for AC induction motors is an excellent device for powerful, yet quiet, pump operation. Designed for use with a capacitor-start/capacitor-run motor, it includes active power factor correction (PFC) and inrush current limiting. This is the drive unit. A Microchip Technology dsPIC30F2020 and all of the control circuitry is at the upper right, with all of the power components below. The line filter and low-voltage supplies are in a separate box to the left. It’s designed to sit vertically with the three large filter capacitors at the bottom, so they stay as cool as possible.

Richard named his finished network control system the “Net Butler.” This innovative multifunctional design can control, monitor, and automatically maintain a home network. Built around a WIZnet iMCU7100EVB, the design has several functions, such as reporting on connected network devices and downloading Internet-based content.

I last saw Richard in March 2012 at the Design West Conference in San Jose, CA. As usual, he stopped by our booth to chat about his work and Circuit Cellar magazine in general. He had a great passion for both, and it showed whenever I spoke with him. He was a true believer of this magazine and its mission. During our chat, he asked if he could write about the seven-processor Intel Industrial Control Robotic Orchestra system on display at the conference. I agreed, of course! His enthusiasm for doing such an article was apparent. Soon thereafter he was at the Intel booth taking photos and notes for his column.

I’m happy to announce that the column—which he titled “EtherCAT Orchestra”—will appear in Circuit Cellar 264 (July 2012).

Richard’s work was a wonderful contribution to this magazine, and we’re grateful to have published his articles. We’re sure Richard’s inventive design ideas and technical insight will endure to help countless more professionals, academics, and students to excel at electronics engineering for years to come.

Wireless Data Control for Remote Sensor Monitoring

Circuit Cellar has published dozens of interesting articles about handy wireless applications over the years. And now we have another innovative project to report about. Circuit Cellar author Robert Bowen contacted us recently with a link to information about his iFarm-II controller data acquisition system.

The iFarm-II controller data acquisition system (Source: R. Bowen)

The design features two main components. Bowen’s “iFarm-Remote” and the “iFarm-Base controller” work together to as an accurate remote wireless data acquisition system. The former has six digital inputs (for monitoring relay or switch contacts) and six digital outputs (for energizing a relay’s coil). The latter is a stand-alone wireless and internet ready controller. Its LCD screen displays sensor readings from the iFarm-Remote controller. When you connect the base to the Internet, you can monitor data reading via a browser. In addition, you can have the base email you notifications pertaining to the sensor input channels.

You can connect the system to the Internet for remote monitoring. The Network Settings Page enables you to configure the iFarm-Base controller for your network. (Source: R. Bowen)

Bowen writes:

The iFarm-II Controller is a wireless data acquisition system used to remotely monitor temperature and humidity conditions in a remote location. The iFarm consists of two controllers, the iFarm-Remote and iFarm-Base controller. The iFarm-Remote is located in remote location with various sensors (supports sensors that output +/-10VDC ) connected. The iFarm-Remote also provides the user with 6-digital inputs and 6-digital outputs. The digital inputs may be used to detect switch closures while the digital outputs may be used to energize a relay coil. The iFarm-Base supports either a 2.4GHz or 900Mhz RF Module.

The iFarm-Base controller is responsible for sending commands to the iFarm-Remote controller to acquire the sensor and digital input status readings. These readings may be viewed locally on the iFarm-Base controllers LCD display or remotely via an Internet connection using your favorite web-browser. Alarm conditions can be set on the iFarm-Base controller. An active upper or lower limit condition will notify the user either through an e-mail or a text message sent directly to the user. Alternatively, the user may view and control the iFarm-Remote controller via web-browser. The iFarm-Base controllers web-server is designed to support viewing pages from a PC, Laptop, iPhone, iTouch, Blackberry or any mobile device/telephone which has a WiFi Internet connection.—Robert Bowen,

iFarm-Host/Remote PCB Prototype (Source: R. Bowen)

Robert Bowen is a senior field service engineer for MTS Systems Corp., where he designs automated calibration equipment and develops testing methods for customers involved in the material and simulation testing fields. Circuit Cellar has published three of his articles since 2001:

Design West Update: Intel’s Computer-Controlled Orchestra

It wasn’t the Blue Man Group making music by shooting small rubber balls at pipes, xylophones, vibraphones, cymbals, and various other sound-making instruments at Design West in San Jose, CA, this week. It was Intel and its collaborator Sisu Devices.

Intel's "Industrial Controller in Concert" at Design West, San Jose

The innovative Industrial Controller in Concert system on display featured seven Atom processors, four operating systems, 36 paint ball hoppers, and 2300 rubber balls, a video camera for motion sensing, a digital synthesizer, a multi-touch display, and more. PVC tubes connect the various instruments.

Intel's "Industrial Controller in Concert" features seven Atom processors 2300

Once running, the $160,000 system played a 2,372-note song and captivated the Design West audience. The nearby photo shows the system on the conference floor.

Click here learn more and watch a video of the computer-controlled orchestra in action.

Robot Design with Microsoft Kinect, RDS 4, & Parallax’s Eddie

Microsoft announced on March 8 the availability of Robotics Developer Studio 4 (RDS 4) software for robotics applications. RDS 4 was designed to work with the Kinect for Windows SDK. To demonstrate the capabilities of RDS 4, the Microsoft robotics team built the Follow Me Robot with a Parallax Eddie robot, laptop running Windows 7, and the Kinect.

In the following short video, Microsoft software developer Harsha Kikkeri demonstrates Follow Me Robot.

Circuit Cellar readers are already experimenting Kinect and developing embedded system to work with it n interesting ways. In an upcoming article about a Kinect-based project, designer Miguel Sanchez describes a interesting Kinect-based 3-D imaging system.

Sanchez writes:

My project started as a simple enterprise that later became a bit more challenging. The idea of capturing the silhouette of an individual standing in front of the Kinect was based on isolating those points that are between two distance thresholds from the camera. As depth image already provides the distance measurement, all the pixels of the subject will be between a range of distances, while other objects in the scene will be outside of this small range. But I wanted to have just the contour line of a person and not all the pixels that belong to that person’s body. OpenCV is a powerful computer vision library. I used it for my project because of function blobs. This function extracts the contour of the different isolated objects of a scene. As my image would only contain one object—the person standing in front of the camera—function blobs would return the exact list of coordinates of the contour of the person, which was what I needed. Please note that this function is a heavy image processing made easy for the user. It provides not just one, but a list of all the different objects that have been detected in the image. It can also specify is holes inside a blob are permitted. It can also specify the minimum and maximum areas of detected blobs. But for my project, I am only interested in detecting the biggest blob returned, which will be the one with index zero, as they are stored in decreasing order of blob area in the array returned by the blobs function.

Though it is not a fault of blobs function, I quickly realized that I was getting more detail than I needed and that there was a bit of noise in the edges of the contour. Filtering out on a bit map can be easily accomplished with a blur function, but smoothing out a contour did not sound so obvious to me.

A contour line can be simplified by removing certain points. A clever algorithm can do this by removing those points that are close enough to the overall contour line. One of these algorithms is the Douglas-Peucker recursive contour simplification algorithm. The algorithm starts with the two endpoints and it accepts one point in between whose orthogonal distance from the line connecting the two first points is larger than a given threshold. Only the point with the largest distance is selected (or none if the threshold is not met). The process is repeated recursively, as new points are added, to create the list of accepted points (those that are contributing the most to the general contour given a user-provided threshold). The larger the threshold, the rougher the resulting contour will be.

By simplifying a contour, now human silhouettes look better and noise is gone, but they look a bit synthetic. The last step I did was to perform a cubic-spline interpolation so contour becomes a set of curves between the different original points of the simplified contour. It seems a bit twisted to simplify first to later add back more points because of the spline interpolation, but this way it creates a more visually pleasant and curvy result, which was my goal.


(Source: Miguel Sanchez)
(Source: Miguel Sanchez)

The nearby images show aspects of the process Sanchez describes in his article, where an offset between the human figure and the drawn silhouette is apparent.

The entire article is slated to appear in the June or July edition of Circuit Cellar.

Aerial Robot Demonstration Wows at TEDTalk

In a TEDTalk Thursday, engineer Vijay Kumar presented an exciting innovation in the field of unmanned aerial vehicle (UAV) technology. He detailed how a team of UPenn engineers retrofitted compact aerial robots with embedded technologies that enable them to swarm and operate as a team to take on a variety of remarkable tasks. A swarm can complete construction projects, orchestrate a nine-instrument piece of music, and much more.

The 0.1-lb aerial robot Kumar presented on stage—built by UPenn students Alex Kushleyev and Daniel Mellinger—consumed approximately 15 W, he said. The 8-inch design—which can operate outdoors or indoors without GPS—featured onboard accelerometers, gyros, and processors.

“An on-board processor essentially looks at what motions need to be executed, and combines these motions, and figures out what commands to send to the motors 600 times a second,” Kumar said.

Watch the video for the entire talk and demonstration. Nine aerial robots play six instruments at the 14:49 minute mark.

Zero-Power Sensor (ZPS) Network

Recently, we featured two notable projects featuring Echelon’s Pyxos Pyxos technology: one about solid-state lighting solutions and one about a radiant floor heating zone controller. Here we present another innovative project: a zero-power sensor (ZPS) network on polymer.

The Zero Power Switch (Source: Wolfgang Richter, Faranak M.Zadeh)

The ZPS system—which was developed by Wolfgang Richter and Faranak M. Zadeh of Ident Technology AG— doesn’t require battery or RF energy for operation. The sensors, developed on polymer foils, are fed by an electrical alternating field with a 200-kHz frequency. A Pyxos network enables you to transmit of wireless sensor data to various devices.

In their documentation, Wolfgang Richter and Faranak M. Zadeh write:

“The developed wireless Zero power sensors (ZPS) do not need power, battery or radio frequency energy (RF) in order to operate. The system is realized on polymer foils in a printing process and/or additional silicon and is very eco-friendly in production and use. The sensors are fed by an electrical alternating field with the frequency of 200 KHz and up to 5m distance. The ZPS sensors can be mounted anywhere that they are needed, e.g. on the body, in a room, a machine or a car. One ZPS server can work for a number of ZPS-sensor clients and can be connected to any net to communicate with network intelligence and other servers. By modulating the electric field the ZPS-sensors can transmit a type of “sensor=o.k. signal” command. Also ZPS sensors can be carried by humans (or animals) for the vital signs monitoring. So they are ideal for wireless monitoring systems (e.g. “aging at home”). The ZPS system is wireless, powerless and cordless system and works simultaneously, so it is a self organized system …

The wireless Skinplex zero power sensor network is a very simply structured but surely functioning multiple sensor system that combines classical physics as taught by Kirchhoff with the latest advances in (smart) sensor technology. It works with a virtually unlimited number of sensor nodes in inertial space, without a protocol, and without batteries, cables and connectors. A chip not bigger than a particle of dust will be fabricated this year with the assistance of Cottbus University and Prof. Wegner. The system is ideal to communicate via PYXOS/Echelon to other instances and servers.

Pyxos networks helps to bring wireless ZPS sensor data over distances to external instances, nets and servers. With the advanced ECHELON technology even AC Power Line (PL) can be used.

As most of a ZPS server is realized in software it can be easily programmed into a Pyxos networks device, a very cost saving effect! Applications start from machine controls, smart office solutions, smart home up to Homes of elderly and medical facilities as everywhere else where Power line (PL) exists.”

Inside the ZPS project (Source: Wolfgang Richter, Faranak M.Zadeh)

For more information about Pyxos technology, visit

This project, as well as others, was promoted by Circuit Cellar based on a 2007 agreement with Echelon.

Robot Nav with Acoustic Delay Triangulation

Building a robot is a rite of passage for electronics engineers. And thus this magazine has published dozens of robotics-related articles over the years.

In the March issue, we present a particularly informative article on the topic of robot navigation in particular. Larry Foltzer tackles the topic of robot positioning with acoustic delay triangulation. It’s more of a theoretical piece than a project article. But we’re confident you’ll find it intriguing and useful.

Here’s an excerpt from Foltzer’s article:

“I decided to explore what it takes, algorithmically speaking, to make a robot that is capable of discovering its position on a playing field and figuring out how to maneuver to another position within the defined field of play. Later on I will build a minimalist-like platform to test algorithms performance.

In the interest of hardware simplicity, my goal is to use as few sensors as possible. I will use ultrasonic sensors to determine range to ultrasonic beacons located at the corners of the playing field and wheel-rotation sensors to measure distance traversed, if wheel-rotation rate times time proves to be unreliable.

From a software point of view, the machine must be able to determine robot position on a defined playing field, determine robot position relative to the target’s position, determine robot orientation or heading, calculate robot course change to approach target position, and periodically update current position and distance to the target. Because of my familiarity with Microchip Technology’s 8-bit microcontrollers and instruction sets, the PIC16F627A is my choice for the microcontrollers (mostly because I have them in my inventory).

To this date, the four goals listed—in terms of algorithm development and code—are complete and are the main subjects of this article. Going forward, focus must now shift to the hardware side, including software integration to test beyond pure simulation.

A brief survey of ultrasonic ranging sensors indicates that most commercially available units have a range capability of 20’ or less. This is for a sensor type that detects the echo of its own emission. However, in this case, the robot’s sensor will not have to detect its own echoes, but will instead receive the response to its query from an addressable beacon that acts like an active mirror. For navigation purposes, these mirrors are located at three of the four corners of the playing field. By using active mirrors or beacons, received signal strength will be significantly greater than in the usual echo ranging situation. Further, the use of the active mirror approach to ranging should enable expansion of the effective width of the sensor’s beam to increase the sensor’s effective field of view, reducing cost and complexity.

Taking the former into account, I decided the size of the playing field will be 16’ on a side and subdivided into 3” squares forming an (S × S) = (64 × 64) = (26, 26) unit grid. I selected this size to simplify the binary arithmetic used in the calculations. For the purpose of illustration here, the target is considered to be at the center of the playing field, but it could very well be anywhere within the defined boundaries of the playing field.

Figure 1: Squarae playing field (Source: Larry Foltzer CC260)

Referring to Figure 1, the corners of the square playing field are labeled in clockwise order from A to D. Ultrasonic sonar transceiver beacons/active mirrors are placed at three of the corners of the playing field, at the corners marked A, B, and D.”

The issue in which this article appears will available here in the coming days.