MTi 100-series IMU helps Racelogic to achieve breakthrough with new VIPS system for tracking cars’ motion accurately with no satellite signals.

The development and validation of new road vehicles and equipment calls for the precise testing of dynamic behavior including velocity, acceleration, deceleration and attitude. Tests of the safety and performance of new models are generally carried out on dedicated outdoor test tracks. Here, parameters such as acceleration, cornering speed and braking distances can be measured accurately under varied driving conditions.

Nearly all the world’s top manufacturers of cars, and of components such as tires, include data acquisition systems supplied by UK technology pioneer Racelogic in their array of vehicle testing equipment. Racelogic’s VBOX is the automotive industry’s preferred data acquisition system for vehicle testing because of its outstanding performance: it logs at a frequency of 100 times a second the exact position of a test vehicle on the road to an accuracy of ±2cm. It achieves this remarkable accuracy by combining signals from multiple GNSS constellations, such as GPS and GLONASS, with inertial measurements and wheel speed data from the vehicle itself.

The inertial data – measurements in three dimensions of acceleration and of rate-of-turn – are obtained from the high-accuracy Xsens IMU (inertial measurement unit). Racelogic, a long-time customer of Xsens, relies on the MTi series of IMUs because they offer the very high accuracy that Racelogic requires, while being small, light, and easy to integrate into the sensor/receiver unit mounted on the roof of the vehicle under test.

Using sophisticated algorithms developed by Racelogic, the VBOX Data Logger base unit performs post-processing on the measurements recorded during a test run. The outputs from a VBOX IMU enable the VBOX data logger to apply error correction to the raw satellite positioning signals: it is the Racelogic software backed by the MTi series IMU’s measurements which allow the system to achieve ±2cm position accuracy and help it to maintain the accuracy in GPS denied environments.

When a car manufacturer announces that a new model goes from 0mph to 60mph more quickly than its closest competitor, it relies on measurements from the VBOX to validate its claim. In the same way, when it tests the limits of a car’s high-speed cornering, and the speed at which its tires lose grip, it is the VBOX which detects the first few centimeters of deviation as the rear wheels begin to slide. This is why the VBOX system’s accuracy is so highly prized by the automotive industry.

Positioning with no satellite signal

The primary use case for the VBOX system is to support vehicle testing on outdoor test tracks. But some tests that car manufacturers want to perform are either difficult or impossible on an open, outdoor test track. Examples include:

• Testing dynamic behavior when driving through a tunnel, or in other zones which have limited reception of satellite signals, such as urban canyons and in dense forest.
• Testing the operation of park assist and other driver assistance systems in a multi-story car park or indoor test chamber
• Tire testing on an ice rink

To meet this demand, Racelogic has developed a new indoor positioning system which enables the testing and validation of ADAS sensors, autonomous vehicles and vehicle dynamics indoors. Called the VBOX Indoor Positioning System (VIPS), the equipment achieves the same positional accuracy – ±2cm – as the standard VBOX system, without any satellite signal input. This accuracy is unprecedented in the high-precision world of automotive testing: even the best competing indoor positioning products on the market are only able to achieve accuracy of ±5cm.

As well as supporting any indoor test use case, the VIPS product also enables Racelogic to provide an integrated indoor/outdoor system for VBOX users. It is the world’s first indoor positioning system to provide a seamless transition between GPS-based and indoor position measurement systems with no loss of accuracy.

IMU data ensure high accuracy

The technology which enables Racelogic to achieve such high positional accuracy when out of range of satellite positioning signals is similar in its operation to the outdoor system. But the VIPS system relies on an array of six or more Ultra-Wideband (UWB) static radio beacons mounted at intervals of around 50m to provide the raw position information. A ‘Rover’ sensor unit mounted on the roof of the vehicle under test receives the UWB signals from multiple beacons simultaneously. The Rover unit also contains an MTi-100 series IMU module from Xsens: this provides extremely accurate, synchronized acceleration and rate-of-turn measurements at an output data rate of up to 2kHz.

And as with satellite positioning signals, the VBOX Indoor Positioning System software uses the MTi 100-series module’s acceleration and rate-of-turn data to perform error correction on the UWB signals. The combination of UWB data, IMU data and Racelogic’s unique software produces the VIPS product’s ±2cm accuracy on which automotive manufacturers rely.

Flexible and scalable system

The UWB beacons used in the VIPS product may be battery-powered to allow for positioning on any surface. An installation can include up to 250 beacons, making the system scalable for coverage of a wide surface area. This scalability is particularly useful in applications such as underground mines or construction sites.

The VIPS equipment can measure vehicle velocity up to 270km/h. The accuracy of velocity measurements is ±0.1km/h.

Julian Thomas, Founder and Managing Director of Racelogic, said: ‘The top priority for Racelogic in developing the VIPS solution was to achieve the industry’s best guaranteed accuracy indoors, in any terrain and any driving conditions – customers have relied on Racelogic for superior accuracy ever since the launch of the VBOX data acquisition system in 2001.

‘That’s why we chose the MTi 100-series IMU from Xsens. Our evaluation showed it provided the most accurate inertial sensor data of any module in its class, enabling our VIPS solution to maintain guaranteed accuracy across the entire measured area.’

For more information about the Racelogic VIPS system, go to the VBOX Indoor Positioning website.

A life-saving innovation: new technology to locate first responders indoors
depends on mini Xsens AHRS’s stable measurements

When rescue service personnel go to the aid of people trapped in a burning or unsafe building, they are entering the unknown: they do not know what danger they will face, or where the obstacles stand between them and the people they have come to save. And in a fire or after an earthquake, first responders are often quickly disorientated inside a building.

Emergency services personnel, soldiers, and others could operate more quickly and safely if they had aid to navigation inside an unknown building. But indoors, GPS signals are unavailable or patchy. So how can people’s position be tracked indoors, in a tunnel or underground, in the absence of satellite navigation?

This was the challenge that the Canadian government asked a team of experts in the Embedded and Multi-sensor Systems Lab (EMSLab) at Ottawa’s Carleton University to solve. The system that they developed has a special motion tracker at its heart. Small in size but big in importance, the MTi-300 Attitude and Heading Reference System (AHRS) from Xsens provides a secure foundation for the operation of a sophisticated array of radio and optical sensors which build a 3D map of any building as the operator moves through it.

The EMSLab system’s camera, LiDAR sensor, and UWB receiver each use an MTi-300 AHRS to provide a consistent 3D frame of reference

How to navigate without a map

The Canadian government’s specification for the Carleton University research project was as hard as it gets in the world of SLAM (Simultaneous Location and Mapping) technology: to precisely track a person’s motion through 3D space, in any indoor location, in real-time, with no map or plan available before entering the building.

To do this, the Carleton University research group developed portable apparatus to be carried by each person who is to be tracked. This apparatus consists of an array of radio, optical, and motion sensors working in concert. Project leader Mohamed Atia, Associate Professor in the Systems and Computer Engineering faculty at Carleton University, says, ‘To track the location of individuals in 3D space, we made a single, multi-sensor system which can be carried or worn by a person. The system we developed is comprised of a vision camera, a LiDAR laser sensor for ranging and object detection, and an ultra-wideband (UWB) receiver, which locates the individual in 3D space relative to UWB beacons dropped at intervals as the operator moves through the building.’

In combination, these technologies are capable of creating a 3D, multi-story map showing obstacles such as walls, windows, doors, and floors, and of positioning the carrier within the map. The way the system creates a 3D map in real-time can be seen in the video below.

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The biggest technical difficulty in implementing this system is to combine the multiple sensor inputs – the process of sensor fusion. Since the Carleton University system is worn or carried, it is continually rising, falling, rotating, and tilting in 3D space as the operator walks, crawls, or runs. Uncorrected, this pitch, roll, and yaw movements make the LiDAR, camera, and UWB inputs inconsistent with each other, and inconsistent with their own outputs over time.

The solution: a stable, accurate 3D frame of reference. And this is provided by three MTi-300 AHRS units. An MTi-300 AHRS affixed to each of the LiDAR sensor, camera, and UWB receiver measures in millimetre-level detail every roll, pitch, and yaw displacement at each sensor, enabling real-time continuous compensation of the sensor’s outputs. This means that they can be fed into a map that is always flat relative to the earth’s surface, no matter what position the carrier’s body is in when each sensor measurement is taken.

Mohamed Atia says, ‘The crucial requirements for the AHRS were accuracy and stability. Even tiny errors in the 3D frame of reference provided by the AHRS are rapidly amplified over the course of a mission, so we needed our chosen AHRS to be accurate, and to maintain its accuracy over time and temperature with almost zero drift. To fit the portable nature of the apparatus, it also needed to be small and light.

‘We studied the market for commercial IMUs carefully, and our evaluation showed that the MTi-300 sensor from Xsens offered the best combination of high performance and small size.’

The Carleton University system has one other clever trick up its sleeve: users wear the MTw Awinda wireless motion capture system, also from Xsens, which allows the system to recognize types of motion, such as motion and crawling, and to perform dead reckoning in the temporary absence of UWB signals. Mohamed Atia says that wireless technology is an important feature of the Awinda product because it makes the SLAM system more easily wearable. He adds, ‘The MTw Awinda system also performs synchronized data sampling accurate to ±10µs, which gives us a time reference for the fusion of all the other sensors in the system.’

A life-saving innovation

Early field trials of the portable Carleton University system prove in principle that accurate, reliable SLAM can be implemented in any indoor 3D space without satellite positioning signals. Mohamed Atia’s hope is that, after further refinement, this technology will one day help save lives. ‘In the military, industrial or emergency services settings, the ability to know exactly where personnel is inside a building could be a game-changer,’ he says. ‘When a first responder is injured or calls for assistance, colleagues will know exactly where to go, and so personnel can be deployed precisely where and when they are needed. In stressful environments such as a building fire or the battlefield, speed saves lives. Our technology, with the MTi-300 at its heart, will enable people to be found and helped more quickly.’

About MTi-300 AHRS

Would you like to know more about the Xsens MTi-300 AHRS? Please visit the product page or the Farnell MTi-300 page

Xsens Product page MTi-300 AHRS

For the avid golfer, perfecting your swing can take hours of dedicated focus and practice. In golf, the difference between a slice and a great shot can come down to tiny, and often unseen, flaws in technique, frequently resulting from an errant swing path learned habitually over time. These underlying problems can be hard to identify and resolve.

deWiz, a revolutionary wearable technology created by Christian Bergh and Markus Westerberg, helps solve this problem by providing in-depth, real-time swing data using Xsens’ precise motion tracking technology. Located within a device worn like a watch, the sensor tracks and analyzes the golfer’s swing, and is coupled with deWiz’s patented Learning Stimuli that provide instantaneous feedback via a small electric pulse and audible alert.

We spoke with deWiz co-founder and Chief Technology Officer Markus Westerberg to find out more about how Xsens is powering the innovation behind this revolutionary new swing modifier for golf.

Getting into the swing of things

The idea behind deWiz was conceived several years ago when Christian was trying to eliminate the slice within his swing. At Ljunghusen Golf Club in Sweden, Christian hit two slices out-of-bounds on the 18^th hole and hit himself on his forehead. That is when he came up with the idea to deliver feedback via a device during his swing, not afterward. After discussing with Markus, they started to pursue developing a training accessory that could provide clear physical prompts, conditioning the mind to perform the correct movements.

After researching the market extensively, the pair decided to build their own device from the ground up, utilizing Xsens’ MTi-1 sensor technology to produce the first proof of concept in 2017. Fast forward to 2021, and deWiz has now gone to market with its eCommerce platform at deWiz.

“There are many gadgets on the market that assist in performing a swing, ensuring that the player uses the correct movement while in use. The problem with these sorts of devices is, once removed, the technique breaks down and the old swing habits return. That’s why we wanted to be able to tap into the subconscious mind, where the memory of a movement resides,” explained Markus.

Inside the device, there is a low-powered sensor used to identify when the golfer is about to take a swing. Once this has been identified, the Xsens MTi-1 sensor is activated – deWiz uses this concept to minimize power consumption. The low-drift capabilities inherent to the Xsens sensor’s technology means deWiz can measure a swing nearly instantly with precision under ±1cm in a 3D space.

How it works

deWiz is adapted specifically for golf swing movements. When the user puts on the wearable device on their wrist, the Xsens sensor accurately tracks the user’s movement pattern, which allows the deWiz algorithm to instantly ascertain any flaws in the swing technique. Within milliseconds of performing the swing, Learning Stimuli feedback in the form of a small electrical pulse on the underside of the wearable alerts the brain of a flawed swing, allowing a golfer to modify their swing pattern

“deWiz provides a primary user experience because of the real-time feedback. Other swing analysis tools have secondary experiences that require looking at a screen or looking at data and translating that data into functional motion. While this has benefits, it’s ultimately a trial-and-error process and a secondary experience. deWiz provides instant feedback – the logic is based firmly on the user’s ability to learn at a faster speed because they know precisely where their swing is going astray and their brain can rescript their swing pattern exponentially faster,” said Markus.

The aim of deWiz is to enhance the user’s performance and the experience between students and coaches. Data is stored and presented within the deWiz app, which makes tracking technique over time straightforward – it’s even possible to favorite well-performed swings and use that data as a benchmark for comparison. Coaches can even gain access to a student’s data and provide feedback from a remote location when they’re not completing sessions together in person.

The technology is built with experienced golfers in mind, providing a heightened level of analysis that’s very difficult to obtain without motion sensor technology. Bryson DeChambeau, Lydia Ko, Annika Sörenstam, Vijay Singh, and Henrik Stenson are just a few examples of some of the professional golf ambassadors consulted during the testing and development of deWiz.

“We couldn’t have built deWiz successfully with other technology – the Xsens MTi sensor brought us hope. When we found Xsens, it was already at the level we were aiming to reach. The accuracy is incredible,” said Markus.

Currently, in the early phases of launching deWiz, Markus has future plans to expand the platform’s interface, adding functions suitable for beginners. There’s even the possibility of expanding the platform to other sports with similarly repetitive movements.

Xsens Product Selector

Want to know the right inertial measurement unit for your application? Try our product selector and find out what MTi you need.

Product selector

Once you find the right product for your application, visit our Farnell Xsens page

Note: For an overview of the differences between MTi 1-series hardware versions 1.x and 2.x, please see: Migration to Hardware Version 2.0 of the MTi 1-series

Due to global constraints in the supply of MEMS components and consequently to ensure continuity of supply of pin compatible MTi 1-series products, new sensing elements are incorporated in the hardware design of the MTi 1-series portfolio. This results in the availability of hardware version 3 of the MTi 1-series. This version will be available next to the current hardware version 2. Production of hardware version 3 will start in August 2021. In addition, the MTi 1- series’ part number naming is changing to a new format. This document provides all practical information that is important for users that are migrating from hardware version 2 to hardware version 3.

Version identification

The hardware version of MTi 1-series modules can be determined in different ways, both visually and through software. The visual differences between hardware version 2 and 3 can be found in the Hardware section of this migration article. For an overview of all (past and current) hardware versions, please refer to the MTi 1-series Datasheet.

In order to identify the hardware version of an MTi 1-series module through software, the ReqHardwareVersion low-level (Xbus) command can be used. For more information, refer to the Low-Level Communication Protocol Document. The hardware version is also displayed in the Device Settings window of MT Manager.

Finally, the hardware version can be derived from the part number of your MTi module, as described in the next paragraph.

Purchasing

The products with the new hardware come with new part numbers. Please add these new part numbers, as described in Table 1, to your purchasing system.

Table 1: Current and new part numbering.
Note: "0" is a number (zero), "I" is a character (capital i).

Note: for ordering, add -T, -C, -R behind the part number to indicate packaging options (not applicable to DKs):
-T = tray of 20 pcs
-C = tray of 100 pcs
-R = reel of 250 pcs

Hardware

The pinout and form factor of the MTi 1-series has remained the same, and will also remain the same during future hardware updates.

Hardware version 3.x introduces new accelerometers and gyroscopes compared to version 2.x. The magnetometer component has remained the same. Table 2 and Table 3 report comparisons of all specifications for the gyroscope and accelerometer components.

Table 2: Gyroscope specifications of MTi 1-series v2.x and v3.x.

Table 3: Accelerometer specifications of MTi 1-series v2.x and v3.x.

Because of the updated hardware components, the hardware layout of the MTi 1-series module has changed, see Figure 1. This also has consequences for the origin of measurements (Figure 2).

Figure 1: Component placement change of the MTi 1-series module. Left: HW version 2.x. Right: HW version 3.x.
All dimensions are in mm. General tolerances are +/- 0.1 mm.

Figure 2: Sensor frame origin change of the MTi 1-series module. Left: HW version 2.x. Right: HW version 3.x.
All dimensions are in mm. General tolerances are +/- 0.1 mm.

Please note that the MTi 1-series module is designed to be embedded into a PCB design through re-flow soldering. Using a (PLCC28) socket to mount the MTi is possible, but this will create mechanical stress on the PCB which can lead to a decreased performance of the module's sensing components. For further information on hardware integration, please refer to our MTi 1-series Hardware Integration Manual.

Sensor fusion performance

The integration of new hardware components does not result in a change in the sensor fusion performance of the VRU, AHRS and GNSS/INS models (MTi-2, -3 and -7), as the sensor fusion algorithms have remained the same. This was proven by various tests during which we compared the estimation accuracy of both the v2 MTi 1-series and the v3 MTi 1-series against a highly accurate (tactical grade) reference.

Software

The communication protocol (Xbus) and communication interfaces (UART, SPI, I²C) have remained unchanged. Software-wise the only difference is that the maximum output rate of the High-Rate data outputs AccelerationHR and RateOfTurnHR have increased to 1000 Hz (previously 800 Hz).

As described in the previous paragraph, the MTi 1-series v3.x are equipped with a different type of gyroscope component. Although the performance of this component is similar to, and in some aspects, better than the component used in the MTi 1-series v2.x, during testing this new gyroscope component has shown slightly lower consistency regarding its initial bias error, a parameter that cannot be compensated for during factory calibration. As a best practice we therefore recommend to initiate a Manual Gyro Bias Estimation shortly after powering up the MTi in order to achieve the best possible orientation performance. Manual Gyro Bias Estimation commands can be automatically sent by your host device by making use of our Device API or low-level (Xbus) communication.

The MTi 1-series v3.x are fully supported by MT Software Suite version 2021.2 and higher. The latest version can be downloaded at: https://www.xsens.com/software-downloads

Firmware

All MTi 1-series with hardware version v3.x will be produced and released with firmware version 1.14.0. It is not possible to downgrade to older firmware versions released for versions 2.x or 1.x.

Documentation

The latest available documentation can always be found at https://www.xsens.com/xsens-mti-documentation. At the start of August the three main documents for the MTi 1-series will be updated for this new release:

• MTi 1-series Datasheet
• MTi 1-series Development Kit User Manual
• MTi 1-series Hardware Integration Manual

Older versions of these documents can be found on this page.

Support

Do you have questions? Please contact our team of product specialists or your local sales representative for more information.

Introduction

The Raspberry Pi is an ARM-based mini PC that is amongst other applications used for prototyping and development of robotics. In this article we will explain how to connect your Xsens MTi device to a Raspberry Pi, and how to easily communicate with it by using our MT Software Development Kit (MT SDK).

Raspberry Pi boards run on ARM Cortex CPUs, which means that they are not compatible with the regular Xsens Device API. Fortunately, Xsens has made a large part of the API open source, allowing users to develop applications for ARM-based platforms as well. Xsens provides C++ example codes as well as a ROS driver that make use of this open source API.

We have used the Raspberry Pi 4 Model B for this article, but the guidelines can also be used for other Raspberry Pi models. Xsens has tested the following motion trackers with the Raspberry Pi:

• MTi 1-series Development Kit (USB, UART)
• MTi 600-series Development Kit (USB, UART)
• MTi 10-series (USB)
• MTi 100-series (USB)

Setup

Start by downloading the latest MT Software Suite for Linux from our website and unpack the .tar.gz package at your desired location. Then, install the MT SDK:

sudo ./mtsdk_linux-xxx_xxxx.x.x.sh 

This article will cover two hardware interfaces of the Raspberry board: USB and TTL UART. If possible, we recommend using USB as a starting point, to verify that your hardware and software can detect and communicate with external sensors. Simply connect your MTi to one of the USB ports of the Raspberry using the USB cable included in your Development Kit.

1. C++ example codes

Inside the MT SDK you will find an examples folder. Open it and navigate to the xda_public_cpp folder. You will find two example codes:

• example_mti_receive_data: Scans for, and connects with MTi devices, configures their outputs, and prints/logs the received data.
• example_mti_parse_logfile: Opens a .mtb log file and parses its contents.

In this folder, open a terminal and build the example codes:

sudo make

Note: If you are using the MTi 10-series or MTi 100-series with a direct USB cable, make sure to have libusb installed, and build the examples using:

sudo make HAVE_LIBUSB=1

You should end up with two executable files, one for each example code. Upon executing example_mti_receive_data your connected MTi should be detected automatically. We refer to the Troubleshooting section of this article if the MTi is not detected.

2. ROS driver

Inside the MT SDK you will find the xsens_ros_mti_driver. Simply follow the README.txt file inside this folder or our guidelines at http://wiki.ros.org/xsens_mti_driver to install and launch the ROS driver. Your MTi should be detected automatically, and a variety of data topics are available to subscribe to. We refer to the Troubleshooting section of this article if the MTi is not detected.

Note: the ROS driver publishes data, but unlike the C++ example code, it does not actually configure the outputs of the MTi. Use the C++ example code or a PC with our GUI MT Manager to configure the MTi such that it outputs the data that are required for your application.

Serial hardware interfaces

Next to the plug-and-play USB interface, Raspberry Pi boards offer various other interfaces that allow you to communicate with MTi devices. For this article we used the mini UART interface that is accessible via the GPIO pins 14 (TXD) and 15 (RXD). We also used the 5V/3V3 and Ground pins to power the MTi.

Note: The configuration and availability of the UART interface varies between Raspberry Pi models. For this article we first had to enable the mini UART. Refer to this article for more information.

Note: The UART interface of an MTi 1-series Development Board will be disabled when the board is powered at 5V. Use the 3.3V output of the Raspberry instead.

In Ubuntu, this UART port will show up as /dev/ttyS0. By default, the ROS driver and C++ example code do not scan this location. Fortunately, it is easy to modify the source code such that it scans for your specific location:

Open example_mti_receive_data.cpp (in case of the C++ example code) or xsens_ros_mti_driver/src/xdainterface.cpp (in case of the ROS driver) and replace the following lines:

XsPortInfoArray portInfoArray = XsScanner::scanPorts();

XsPortInfo mtPort;

for (auto const &portInfo : portInfoArray) { if (portInfo.deviceId().isMti() || portInfo.deviceId().isMtig()) { mtPort = portInfo; break; } }

with

XsPortInfo mtPort = XsScanner::scanPort("/dev/ttyS0",XBR_230k4); 

...where in this case we scan "/dev/ttyS0" for an MTi device that is configured at a baud rate of 230400 bps.

Alternatively, the ROS driver also allows you to configure the desired port and baud rate manually without modifying the source code. To do so, uncomment and modify the following lines in the file xsens_mti_node.yaml, located at xsens_ros_mti_driver/param:

# port: '/dev/ttyS0' # baudrate: 921600

You should now be able to detect and access the MTi via the UART interface.

Troubleshooting

• “No MTi device found.” or “Could not open port.”

  • Ensure that you have the rights to access the port of the MTi (e.g. /dev/ttyUSB0). If you are using the C++ example code, you can check this by executing the code with sudo. Possibly you are not in the right group to access the port of the MTi. See MTSDK.README, located in your MT SDK folder, for further guidelines on changing group access permissions.
  • If you are using the MTi 10-series or MTi 100-series with a direct USB cable, make sure to have libusb installed, and build your code as:

    sudo make HAVE_LIBUSB=1 

  • If you are using a robust MTi 600-series with a USB dongle, make sure to have the relevant drivers installed.
  • If you are not using the USB port or if you are using a custom serial-to-USB converter, try specifying the exact port and baud rate at which your MTi is communicating. See paragraph Serial hardware interfaces of this article.

• My USB-connected MTi does not show up as /dev/ttyUSB#.

  • If you are using the MTi 10-series or MTi 100-series with a direct USB cable, then it is not necessary for the MTi to show up as /dev/ttyUSB#. Make sure to have libusb installed, and build your code as:

    sudo make HAVE_LIBUSB=1 

    The MTi should now be recognized whenever you launch the ROS driver or C++ example code.

• The data I am receiving never reaches the expected data output rate (e.g. 400 Hz).Still facing challenges? Don’t hesitate to contact our Field Application Engineers for further support.

  • We have noticed that the ROS node can cause a high CPU load, leading to lower data output rates. This issue has been fixed in ROS nodes available in MTSS2019.3.2 and later. We recommend migrating to the latest version.
  • If you have connected the MTi via the USB interface, we recommend enabling the low latency mode using setserial. See this page for more details.

• Still facing challenges? Don’t hesitate to contact our Field Application Engineers for further support.

Introduction

This article describes how to interface your MTi 1-series Development Kit with an Arduino for prototyping and testing. Alternatively, embedded examples for I2C and SPI communication with an STM32 Nucleo board are available as part of the MT Software Suite. For more information, see this article.

An example library for I2C communication with an Arduino was developed by our customer U. Vautier and can be downloaded here. The library was shared and documented in this BASE forum post.

An example library for UART communication with an Arduino was developed by our customer E. Al Khatib and can be downloaded here. The library was shared and documented in this BASE forum post.

Setup - I2C and SPI

We recommend to start by reading the MTi 1-series datasheet as well as chapters 4.1-5.2 of the LLCP document and this article to learn about how to communicate with the MTi 1-series using low-level communication, and I2C/SPI in particular. Note that I2C/SPI communication uses reduced Xbus messages; that is, Xbus messages with Preamble and busID removed.

I2C and SPI communcation with an Arduino is usually done using the Wire.h and SPI.h libraries respectively. It is important to start by reading these pages for a general introduction to these libraries and to determine the pin connections for connecting the MTi 1-series (Development Kit) to your Arduino board.

• For I2C communication:
  • You will need to at least connect the SCL, SDA, GND and VDD lines. See the table below.
  • In addition, pull-up resistors are required for the SCL and SDA lines. These pull-up resistors are already included in MTi 1-series Development Kits of hardware revision 2.4 and later. For hardware revisions 2.3 and below, it is required to add these resistors of 2.7 kΩ externally, connecting SCL/SDA to IOREF of the Arduino. The hardware revision is printed on the bottom side of the Development Kit.
• For SPI communication:
  • You will need to at least connect the MOSI, MISO, SCK, nCS (Arduino: SS), GND and VDD lines. See the table below.
  • In addition, as indicated in the MTi 1-series datasheet, the MTi uses SPI mode 3 and outputs MSB first. The Arduino needs to be configured for this by using the command:

    SPI.beginTransaction(SPISettings(2000000, MSBFIRST, SPI_MODE3));  

In order to enable I2C or SPI communication, the selection switches PSEL0 and PSEL1 on the DK board need to be set. The correct settings are printed on the DK. The address of the DK shield for I2C communication can be set using the ADD0, ADD1 and ADD2 selection pins. When left unconnected, the default address will be 111 (0x6B). For more information, refer to the MTi 1-series DK User Manual.

The correct operation of this setup has been tested and verified with the Arduino Uno and Arduino Due.

Troubleshooting

• Why is my Arduino not receiving all data packets sent by the MTi?
  The MTi 1-series feature a maximum output frequency of 100 Hz for most outputs. If the Arduino is not able to keep up with reading all these data packets, it will skip some of them and data overflow messages (0x42 0x01 0x29 0x95) will be generated in the Notification Pipe. You will need to lower the output frequency of the device, or speed up the Arduino code (for example by reducing the amount of Serial print commands).
  
• Why are the data packets I receive corrupted?
  Improper wiring may cause communication issues. We recommend not using wires longer than 20 cm.
  
• Why are the data packets I receive incomplete?
  By default the Wire.h library makes use of 32-byte buffers. This means that the last part of packets with a length of more than 32 bytes will be dropped. It is possible to increase the buffer size, i.e. by modifying the Wire.h library files. For further help, please refer to the Arduino forums.
  
• I cannot upload my Arduino code when the MTi 1-series Shield Board is mounted onto the Arduino.
  The UART pins of the Development Kit can interfere with the Arduino programmer. Ensure that the selection switches PSEL0 and PSEL1 on the DK board are set correctly. If the problem persists, instead of stacking the Development Kit onto the Arduino directly, try using wires to connect the necessary I2C/SPI lines and check whether that solves the issue.
  
• How can I change the address for I2C communication using my Arduino?
  Connect the ADD# pins of your MTi 1-series DK to digital I/O pins of your Arduino and in your Sketch configure these I/O pins as output. You can then use digitalWrite() to set the address for I2C communication. Note that the MTi determines its address directly upon startup. This means that when the DK powers up (i.e. using the supply of the Arduino or through a reset of the MTi), the digital I/O pins must already be defined and configured.
  
• How can I modify the example in the I2C  Arduino library to output a different set of data?
  The library comes with an example which outputs Orientation, Acceleration, Magnetic Field and Rate Of Turn data. In order to output different measurement data you should modify the Arduino example. To modify the Arduino example you can follow the instructions in this BASE forum post.

• I am still having problems with this example or low-level communication in general.
  Feel free to ask your questions on our Community Forum, or simply comment on this blog. Xsens staff will try to help you as soon as possible. Alternatively, you can request private technical support here.

When selecting components, the parameters of size and weight are generally at or near the top of an aircraft designer’s list of priorities. Space is always limited inside an airframe. And the lighter the aircraft, the less power and fuel are required to lift it into the sky and keep it airborne.

So aerospace engineers are frequently tasked with reducing the size and weight of a component or sub-system. This often calls for the evaluation of new, advanced materials, or a radical re-thinking of an engineering design or process.

When CDO Technologies was invited by the US government to develop a prototype of a novel TSPI (Time and Space Positioning Information) flight test module, however, the hardware design turned out to be rather more straightforward. CDO’s prototype for a much smaller, lighter TSPI module for light aircraft comprised a strip of adhesive tape, an off-the-shelf rugged tablet and GPS antenna, and a matchbox-sized motion sensor from Xsens.

That unit from Xsens, an MTi-G-710 GNSS/INS inertial navigation system measuring just 57mm x 42mm x 23.5mm, provides the complete set of motion measurements and GPS signal required to track the attitude, position and altitude of an aircraft in real time. When combined with dedicated flight test data logging software developed by CDO, the prototype system was impressive enough to merit support for further development.

Electronics replaces mechanics

The trigger for CDO to develop its novel flight test system was dissatisfaction with existing stand-alone TSPI systems in use, particularly in smaller aircraft. A TSPI system is a fundamental element in any flight test: when testing an aircraft’s systems, such as communications, flight controls or engines, the TSPI provides a baseline for an understanding of the operation of the system under test, enabling the test engineer to log the behavior of aircraft systems at known speed, acceleration, altitude and attitude.

Today, most large commercial aircraft have built-in TSPI instrumentation to support flight testing. But smaller or cheaper planes do not, and so flight testing in them requires the use of a dedicated TSPI instrument. TSPI instrumentation in general use in commercial aviation today is based on a Fiber-Optic Gyroscope (FOG), a mechanical device which has traditionally been favored because of the reliable accuracy of its attitude and position measurements.

But an FOG has three main drawbacks in aerospace applications:

• It is large, so potentially hard to accommodate in a cramped airframe
• It is heavy - its weight presents a potential safety hazard if it accidentally breaks free from its mounting during aircraft maneuvers
• It is prone to over-heating

In addition, TSPI systems based on a conventional FOG typically require a differential GPS satellite positioning receiver for accurate altitude readings. Access to differential GPS signals is available on subscription, but is expensive.

The goal of the new TSPI prototype was to improve on all these features, creating a working design for a TSPI module which was much smaller and lighter than instrumentation in common use today, and avoiding the need to pay for differential GPS subscription. Chris Smith, a research engineer at CDO Technologies, describes the breakthrough that the developers made on learning about the use of Xsens GNSS/INS modules for position measurement in submarines. ‘A submarine, like an aircraft, presents electronic equipment with a challenging operating environment. In many ways, the 3D space in which a submarine operates in is similar to the aerial environment in which aircraft move. And like aircraft, submarines are subject to space constraints, which is why an Xsens motion sensor is attractive in that application.

‘CDO Technologies’ sponsor in the US government had asked us to investigate options for TSPI instrumentation which would be better suited to use in light aircraft - something lighter and smaller than the traditional FOG-based system. With the Xsens motion sensor used in submarines, the answer was staring me in the face. The device is a ready-made sensor system-in-a-box for TSPI systems – it gives all the position measurements needed for TSPI instrumentation, and because it is supplied as an integrated module, the outputs from the device are synchronized and calibrated.’

Inside an MTi-G-710’s shielded enclosure, there are a 3D accelerometer, 3D MEMS gyroscope, 3D magnetometer, GNSS receiver and a barometer, all operating at very high levels of accuracy and precision. It also provides an interface to an external GPS antenna. The MTi-G-710’s sensor fusion software, which intelligently combines each sensor’s outputs, helped to simplify the CDO team’s software development: the output from the MTi-G-710 is a precisely timed stream of roll, pitch, yaw, position, velocity and altitude measurements at a sampling rate of up to 400Hz - all the measurements which are required in TSPI instrumentation.

CDO Technologies’ prototype flight test instrumentation system based on an Xsens MTi motion sensor

Chris and his team then drew on their expertise in flight systems technology to develop a user interface and back-end logging system. The CDO Technologies engineers’ software runs on a standard, rugged Getac tablet. The software provides a user interface for the flight test engineer to monitor the TSPI system outputs in real time during a test flight, and to log the data for post-flight analysis.

Because of the small size of the Xsens sensor and the GPS antenna, installation of the prototype for system testing was simple - the units could simply be taped to the floor of the cabin of the aircraft and plugged into the tablet’s connector.

Chris Smith is delighted with the performance of the prototype. It offers substantial and valuable savings in size and weight over conventional mechanical FOG-based systems. But, he says, the value goes further. First, it can be used with a standard GPS signal, because the altitude (barometer) outputs from the MTi-G-710 support correction of the receiver’s altitude outputs. This saves the cost of the subscription required for a differential GPS receiver.

And overall, the accuracy, precision and reliability of the TSPI measurements produced by the CDO prototype are slightly better than those of much larger and heavier commercial-grade TSPI systems approved for use today.

‘Evaluation of the CDO prototype has been a great success,’ says CDO’s Chris Smith. ‘We have now been invited by the US government to take our prototype forward into advanced system testing with a view to deployment. I’m delighted that we have been able to achieve our goal of reducing the weight, size and cost of TSPI instrumentation. And I’m certain that our development time was considerably shorter than we expected it to be, because the comprehensive functionality and user-friendly outputs provided by the MTi-G-710 sensor simplified both the hardware design and the software interface which we designed to run on the Getac tablet.’

For more information about the R&D and system engineering support services provided by CDO Technologies, go to www.cdotech.com/.

Choosing your product

Want to know the right inertial measurement unit for your application? Try our recommendation tool and find out what MTi you need by answering just 3 questions.

Recommendation tool

Today we introduce two new products to our MTi 600-series. We have extended the choice of rugged MTi's with and without an integrated GNSS satellite positioning receiver.

Meet the new GNSS/INS module, the MTi-670G, and the new rugged AHRS, the MTi-630R. The complete MTi 600-series lineup offers products that are capable of meeting a broad range of application requirements at competitive prices. The new rugged products are particularly well suited to use in harsh environments in maritime, mining, agriculture and many other applications.

Boele de Bie, Xsens’ CEO, said: ‘The latest members of the MTi 600-series are the fruit of Xsens’ continued investment in product development and new technology, ensuring that we provide the combination of performance, features and value that our customers demand across the range of markets we serve, from high-volume mainstream electronics to highly specialized product designs including RTK.’

Rugged housing to withstand harsh environments

The MTi-670G and MTi-630R are housed in an IP68-rated aluminum enclosure which measures 40.9mm x 56.5mm x 36.8mm, and is high vibration- and shock-proof. Both modules feature standard CAN and RS232 interfaces and an output data rate of up to 400Hz.

High-performance accuracy

The new MTi-670G include a high-performance ZED F9 GNSS receiver by u-blox. Xsens' renowned sensor fusion firmware provides absolute positioning accuracy of better than ±1m. The sensor is easy to integrate into system designs thanks to its support for Xbus and standard NMEA and CAN protocols.

The MTi-630R AHRS gives you roll/pitch measurement accuracy of ±0.2°, and heading accuracy of ±1°. It is also easy to integrate into end product designs thanks to the MT Software Suite, which also includes drivers for the LabVIEW, ROS and GO development languages.

All modules in the MTi 600-series offer high-performance features:

• Precise factory calibration of MTI
• High immunity to magnetic interference
• Adaptive firmware operation to optimize performance in various types of applications
• Out-of-the-box operation with Xsens’ popular MTi development (DK) or starter kits (SK)

The MTi-670G and MTi-630R are available for sampling now. Ruggedized versions of the MTi-610 Inertial Measurement Unit (IMU) and MTi-620 Vertical Reference Unit (VRU), the MTi-610R and MTi-620R, are available on request.

Visit the MTi-630R and MTi-670G product pages for more information or visit the online shop for ordering starter kits.

Did you our webinar on the latest GNSS/INS Module "MTi-680G" with cm-accurate outdoor real-time positioning?

No worries! Here you go:

https://www.xsens.com/watch-webinar/outdoor-real-time-3d-positioning

If you are interested in accurate, smooth and real-time outdoor positioning & -orientation for your Autonomous Vehicles, Mobile Robots and Drones then you can watch again our recorded webinar.

This Thursday (29th of April) I will be hosting a technical webinar regarding the latest in RTK + IMU technology for industrial applications!

Learn more about outdoor real-time 3D positioning of Autonomous Vehicles, Mobile Robots and Drones using the highest standard GNSS/INS (Global Navigation Satellite System/Intertial Navigation System) - Xsens MTi-680G

Webinar agenda:

• MTi-680G Intro
• How to receive RTK corrections
• How to configure the MTi-680G
• Real-time data of MTi-680G with RTK accuracy
• Best Practices
• Q&A

April 29th, 11 AM (CET)

If you are interested in learning more check the following link:

https://bit.ly/3vivhRR