EECE5554-Lab 3 Solved

Hardware / Sensors:Vectornav VN-100 IMU. The user manual for the sensor is provided.

Hardware Setup
Imu udev rules  Standard Ubuntu is not designed for roboti application and for fast sensors it may not behave as we want it to. There may be latency in terms of its response to the sensor. There are a set of files under /etc/udev that dictate how Ubuntu will react to certain sensors.

To make the VN-100 plug & play and to address Ubuntu USB latency issues we can do the following

Connect your imu and  type the following command in the terminal

$ dmesg | grep vn100      

If you do not know what those commands mean, check out Linux tutorial.

You will see your sensor attributes including product id and vendor id. If these values differ from the values below, change them in your 50-VN-100.rules file accordingly.

1.       As Sudo create a file under /etc/udev/rules.d called 50-VN-100.rules with the following

KERNEL=="ttyUSB[0-9]*", ACTION=="add", ATTRS{idVendor}=="1d6b", ATTRS{idProduct}=="0002",

MODE="0666", GROUP="dialout"
2.       Ubuntu's default latency of 16ms cause issues with high rate sensors, this can be solved by adding the following UDEV rules as 49-USB-LATENCY.rules

ACTION=="add", SUBSYSTEM=="usb-serial", DRIVER=="ftdi_sio", ATTR{latency_timer}="1"
3.       Once the rules have been added, to get udev to recognize the rule, run the following command:

 sudo udevadm control --reload-rules && sudo service udev restart && sudo udevadm trigger

Finally unplug and replug the VN-100 to have it work with the new rules.

You can verify the applied settings with below command, should report 1 on success.

$ cat /sys/bus/usb-serial/devices/<ttyUSB0  your device path>/latency_timer

Write a device driver for IMU (individual) and do stationary noise analysis
Open serial port with 115200 baudrate. Configure your IMU to output data at 200Hz for this lab.

Parse $vnymr string, to get accel, gyro, orientation (roll, pitch, yaw) and magnetometer data. Refer to sensor user_manual.

Use the standard ROS sensor_msgs/IMU to publish the above data. Convert the above Yaw, Pitch, Roll data into quaternions and publish it as orientation in the same imu msg. Use ROS sensor_msgs/MagneticField to publish magnetometer data.

Begin collecting a time series data (rosbag) for the 3 accelerometers, 3 angular rate gyros, 3axis magnetometers. Collect at least 10-15 min of data with the instrument stationary and as far away as possible from your computer.

Plot each time series in your report and figure out the noise characteristics of each of the values (mean and standard deviation) reported by the IMU.

Allan Variance Data collection and Analysis
For this part we only need to collect one set of data for each team – collect roughly 5 hours worth of stationary IMU data at a location that is not subject to vibrations (passing trains, building sway etc).

The following MathWorks webpage provides code that you can use to analyze your data for Allan variance. We do not need any further analysis for Allan Variance other than that illustrated in this code.

https://www.mathworks.com/help/nav/ug/inertial-sensor-noise-analysis-using-allanvariance.html

You need to analyze this data using the Matlab functions and should be able to answer the following questions.

1.       What kind of errors/sources of noise are present?

2.       How do we model them? Where do we measure them? Can you relate your measurements to the datasheet for the VN100?