Table of content

• Simulation in gazebo

• Add gaussian noise

• Formatting Imu data

• Visualizing

• Files documetation

do note that all commands must be in the work space directory

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Simulation in gazebo

To set up the program use:

 ./setup.sh

This terminal will show the Imu readings

To launch simulation, open up another terminal and write:

 ./start_simulation.sh

To move the bot open up another terminal and do:

./control.sh

The bot moves in automatic mode where pressing any of the W A S D will get it to increase the speed at a certain direction, press the spacebar to stop it completely, press ctrl c to quit the program

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To add gaussian noise

Type:

rospack find turtlebot3_description

The directory that appears copy it and go to it using cd

Afterwards type:

cd urdf

Then type ls to check all the available files, the file we are looking for should be named something similar to turtlebot3_burger.gazebo.xacro.

Type the following command:

sudo nano turtlebot3_burger.gazebo.xacro

scroll down until you see

<plugin name="imu_plugin" filename="libgazebo_ros_imu.so">

replace starting from with the following code

<gazebo>
    <plugin name="imu_plugin" filename="libgazebo_ros_imu.so">
      <alwaysOn>true</alwaysOn>
      <bodyName>imu_link</bodyName>
      <frameName>imu_link</frameName>
      <topicName>imu</topicName>
      <serviceName>imu_service</serviceName>
      <gaussianNoise>0.01</gaussianNoise>
      <imu>
      <angular_velocity>
            <x>
              <noise type="gaussian">
                <mean>0.0</mean>
                <stddev>2e-4</stddev>
                <bias_mean>0.0000075</bias_mean>
                <bias_stddev>0.0000008</bias_stddev>
              </noise>
            </x>
            <y>
              <noise type="gaussian">
                <mean>0.0</mean>
                <stddev>2e-4</stddev>
                <bias_mean>0.0000075</bias_mean>
                <bias_stddev>0.0000008</bias_stddev>
              </noise>
            </y>
            <z>
              <noise type="gaussian">
                <mean>0.0</mean>
                <stddev>2e-4</stddev>
                <bias_mean>0.0000075</bias_mean>
                <bias_stddev>0.0000008</bias_stddev>
              </noise>
            </z>
          </angular_velocity>
          <linear_acceleration>
            <x>
              <noise type="gaussian">
                <mean>0.0</mean>
                <stddev>1.7e-2</stddev>
                <bias_mean>0.1</bias_mean>
                <bias_stddev>0.001</bias_stddev>
              </noise>
            </x>
            <y>
              <noise type="gaussian">
                <mean>0.0</mean>
                <stddev>1.7e-2</stddev>
                <bias_mean>0.1</bias_mean>
                <bias_stddev>0.001</bias_stddev>
              </noise>
            </y>
            <z>
              <noise type="gaussian">
                <mean>0.0</mean>
                <stddev>1.7e-2</stddev>
                <bias_mean>0.1</bias_mean>
                <bias_stddev>0.001</bias_stddev>
              </noise>
            </z>
          </linear_acceleration>
          </imu>
      <updateRate>50</updateRate>
    </plugin>
  </gazebo>

save and exit

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Formatting the Imu data

To turn the Imu data to degrees and apply kalman_filter into the yaw:

./kalman_filter.sh

the above command creates multiple topics which we can read from multiple readings, the topics are:

• /imu_degrees , used to see the orientation imu readings in degrees

• /imu_degrees/yaw used to see the yaw readings in degrees

• /imu_degrees/yaw/filtered used to see the yaw readings after kalman filteration in degrees

• /stable/imu used to see the imu readings in quaternion

• /stable/imu/yaw used to see the yaw readings in quaternion

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To visualize the data

To visualize anything we have to run

To visualize Lidar

Run:

rosrun rviz rviz

Then press add, scroll down until you see the word laser scan afterwards at the display panel (at the left) go to the topic section and enter /scan then go to the global options at the top of the display panel and change the fixed frame to base_scan

To plot the filtered yaw with the noisy yaw

Run:

rqt_multiplot

Press the clog button thats labeled configuration plot, add curves then choose whether you want the filtered data at x or y axis.

Once chosen the axis go to that axis configurations and at topic type /imu_degrees/yaw/filtered, type is float32 and at field choose data float32.

While the other axis go to topic and choose /imu_degrees/yaw, at type choose Float 32 and at field choose data float32, press ok then press run plot at the top right next to the clog

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File content

Scripts

• start_simulation.sh:
  • It sources the package, exports the turtlebot3_model to be burger and initiate the simulation which also initiate the ROS master
• control.sh:
  • like the previous script it sources the package and exports the model to be burger, and it runs the command that allows control of the robot
• kalman_filter.sh:
  • runs the kalman-filter.py file

kalman-filter.py:

Subscribes to the /imu topic, then it takes and converts the imu readings from the /imu topic by using the tf.transformation function for transforming from quaternion to euler, then changes the readings from radian to degree

It publish the conversion to 2 topics, one for the 3 orientation readings called /imu_degrees and the other for the yaw readings called /imu_degrees/yaw, both in degrees

Then it filters the yaw by applying kalman filter, with the new filtered yaw the script publishes it to a new topic called /imu_degrees/yaw/filtered