enav_utilities

enav_utilities

Two main Python fetching classes were created to convert rosbag & aerial map data to generic formats for visualization and/or further processing.

Table of contents

• Aerial maps visualization
• Rosbag data fetching
  • GPS data (& spatial plotting)
  • Images
  • Point clouds
  • Energy consumption
  • Solar irradiance
  • IMU data
  • Encoder data
  • Commanded and estimated velocities

Aerial maps visualization

To load any aerial map, a CSASite instance from csa_raster_load.py needs to be initialized using the path to the directory containing the mapping data. An example showing how to properly use this Python class is shown in the show_raster.py example:

python show_raster.py -d /path/to/raster/directory

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Rosbag data fetching

To load data from a rosbag, a FetchEnergyDataset instance from rosbag_data_load.py needs to be initialized using the path to the said rosbag. Several methods within this class are available to fetch specific data streams.

GPS data (& spatial plotting)

The complete GPS history is accessed through the load_gps_data method documented here. The following sample spatial plot was generated using the plot_gps_data.py sample script:

python plot_gps_data.py -b /path/to/file.bag -d /path/to/raster/directory

Images

Images are accessed through the load_image_data method documented here. The following sample plot was generated using the plot_images.py sample script:

python plot_images.py -b /path/to/file.bag

Point clouds

Similar to images, point clouds can be fetched as numpy arrays by using the load_pointcloud_data method documented here. Note that point clouds are saved in a separate rosbag for each run, so a rosbag different from the one needed for all other data types needs to be loaded.

Energy consumption

The complete power and energy consumption history of the left and right motor drivers onboard the Husky rover base is accessed through the load_energy_data method documented here. The following sample plot was generated using the plot_energy.py sample script:

python plot_energy.py -b /path/to/file.bag

Solar irradiance

The complete solar irradiance history on top of the rover's top plane is accessed through the load_irradiance_data method documented here. The following sample plot was generated using the plot_irradiance.py sample script:

python plot_irradiance.py -b /path/to/file.bag

IMU data

The complete IMU history is accessed through the load_imu_data method documented here. The following sample plot was generated using the plot_imu_data.py sample script:

python plot_imu_data.py -b /path/to/file.bag

Encoder data

The complete encoder history (angular positions and velocities) is accessed through the load_encoder_data method documented here.

Commanded and estimated velocities

Target/commanded velocities were recorded and can be accessed via the load_cmd_vel_data method documented here. Planar velocity estimates of the mobile base were computed from encoder velocities. Those can be accessed through the load_est_vel_data method documented here. The following sample plot was generated using the plot_cmd_est_velocity_data.py sample script:

python plot_cmd_est_velocity_data.py -b /path/to/file.bag