| Name | autonav JSON |
| Version |
1.0.2
JSON |
| download |
| home_page | |
| Summary | Research software for navigating a UAV in indoor environments |
| upload_time | 2024-03-12 18:23:19 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.8 |
| license | MIT |
| keywords |
uav
navigation
indoor
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
[](https://codecov.io/gh/ricardo-s-santos/AutoNAV)
[](https://ricardo-s-santos.github.io/AutoNAV/)
[](https://pypi.org/project/autonav/)
<p align="center">
<img src="https://github.com/ricardo-s-santos/AutoNAV/blob/main/docs/docs/figures/icon.png?raw=true" alt="image" width="200" height="auto">
</p>
A Python package for simulating UAV Navigation in Satellite-Less Environments. The package contains two algorithms the GTRS <a href="https://ieeexplore.ieee.org/document/9456863">[1]</a> and WLS <a href="https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/wss2.12041">[2]</a> whose goal is to estimate and navigate a UAV.
## Installation
Install from PyPI:
```sh
pip install --upgrade pip
pip install autonav
```
## First Steps
After installing the package one can import the algorithms and necessary dependencies as follows:
```python
import matplotlib.pyplot as plt
from autonav import gtrs, wls
from autonav.file_handlers import readpathfile
from autonav.plots import plot_trajectories
from numpy import array
```
Afterwards, one can create the necessary values to run the algorithms:
```python
# Area border
b = 200
# Number of anchors
n = 8
# Position of the anchors
a_i = array(
[
[0, 0, 0],
[0, b, 0],
[b / 2, 0, 0],
[b / 2, b, 0],
[0, 0, b / 8],
[0, b, b / 8],
[b / 2, 0, b / 8],
[b / 2, b, b / 8],]
).T
# Number of measurement samples
k = 50
# Noise standard deviation
sigma = 1
# Maximum velocity allowed to the UAV
v_max = b / 100
# Distance threshold
tau = b / 50
# Smoothing factor
gamma = b / 100
# Initial position of the UAV
initial_uav_position = [10, 10, 5]
# File containing the waypoints
destinations = readpathfile("docs/docs/examples/Path.csv")
```
Finally, run the GTRS or WLS algorithm and plot the trajectories:
```python
# Estimate the trajectory using the GTRS algorithm
[estimated_trajectory, true_trajectory] = gtrs(a_i, n, k, sigma, destinations, initial_uav_position, v_max, tau, gamma)
# Plot the estimated trajectory
plot_trajectories(destinations, [estimated_trajectory], a_i, ['GTRS'])
plt.show()
```
<p align="center">
<img src="https://github.com/ricardo-s-santos/AutoNAV/blob/main/docs/docs/figures/trajectories_plot.png?raw=true" alt="image" width="auto" height="auto">
</p>
## References
[1] J. P. Matos-Carvalho, R. Santos, S. Tomic and M. Beko, "GTRS-Based Algorithm for UAV Navigation in Indoor Environments Employing Range Measurements and Odometry," in IEEE Access, vol. 9, pp. 89120-89132, 2021, doi: 10.1109/ACCESS.2021.3089900. https://ieeexplore.ieee.org/document/9456863
[2] R. Santos, J. P. Matos-Carvalho, S. Tomic and M. Beko, "WLS algorithm for UAV navigation in satellite‐less environments," in IET Wireless Sensor Systems, 2022, 12, (3-4), p. 93-102, DOI: 10.1049/wss2.12041
IET Digital Library, https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/wss2.12041
## License
[MIT License](LICENSE.txt)
Raw data
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"description": "\n[](https://codecov.io/gh/ricardo-s-santos/AutoNAV)\n[](https://ricardo-s-santos.github.io/AutoNAV/)\n[](https://pypi.org/project/autonav/)\n\n<p align=\"center\">\n <img src=\"https://github.com/ricardo-s-santos/AutoNAV/blob/main/docs/docs/figures/icon.png?raw=true\" alt=\"image\" width=\"200\" height=\"auto\">\n</p>\n\nA Python package for simulating UAV Navigation in Satellite-Less Environments. The package contains two algorithms the GTRS <a href=\"https://ieeexplore.ieee.org/document/9456863\">[1]</a> and WLS <a href=\"https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/wss2.12041\">[2]</a> whose goal is to estimate and navigate a UAV.\n\n## Installation\n\nInstall from PyPI:\n\n```sh\npip install --upgrade pip\npip install autonav\n```\n\n## First Steps\n\nAfter installing the package one can import the algorithms and necessary dependencies as follows:\n\n```python\nimport matplotlib.pyplot as plt\n\nfrom autonav import gtrs, wls\nfrom autonav.file_handlers import readpathfile\nfrom autonav.plots import plot_trajectories\nfrom numpy import array\n```\n\nAfterwards, one can create the necessary values to run the algorithms:\n\n```python\n# Area border\nb = 200\n# Number of anchors\nn = 8\n# Position of the anchors\na_i = array(\n [\n [0, 0, 0],\n [0, b, 0],\n [b / 2, 0, 0],\n [b / 2, b, 0],\n [0, 0, b / 8],\n [0, b, b / 8],\n [b / 2, 0, b / 8],\n [b / 2, b, b / 8],]\n ).T\n# Number of measurement samples\nk = 50\n# Noise standard deviation\nsigma = 1\n# Maximum velocity allowed to the UAV\nv_max = b / 100\n# Distance threshold\ntau = b / 50\n# Smoothing factor\ngamma = b / 100\n# Initial position of the UAV\ninitial_uav_position = [10, 10, 5]\n# File containing the waypoints\ndestinations = readpathfile(\"docs/docs/examples/Path.csv\")\n```\n\nFinally, run the GTRS or WLS algorithm and plot the trajectories:\n\n```python\n# Estimate the trajectory using the GTRS algorithm\n[estimated_trajectory, true_trajectory] = gtrs(a_i, n, k, sigma, destinations, initial_uav_position, v_max, tau, gamma)\n# Plot the estimated trajectory\nplot_trajectories(destinations, [estimated_trajectory], a_i, ['GTRS'])\nplt.show()\n```\n\n<p align=\"center\">\n <img src=\"https://github.com/ricardo-s-santos/AutoNAV/blob/main/docs/docs/figures/trajectories_plot.png?raw=true\" alt=\"image\" width=\"auto\" height=\"auto\">\n</p>\n\n## References\n\n[1] J. P. Matos-Carvalho, R. Santos, S. Tomic and M. Beko, \"GTRS-Based Algorithm for UAV Navigation in Indoor Environments Employing Range Measurements and Odometry,\" in IEEE Access, vol. 9, pp. 89120-89132, 2021, doi: 10.1109/ACCESS.2021.3089900. https://ieeexplore.ieee.org/document/9456863\n\n[2] R. Santos, J. P. Matos-Carvalho, S. Tomic and M. Beko, \"WLS algorithm for UAV navigation in satellite\u2010less environments,\" in IET Wireless Sensor Systems, 2022, 12, (3-4), p. 93-102, DOI: 10.1049/wss2.12041\nIET Digital Library, https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/wss2.12041\n\n## License\n\n[MIT License](LICENSE.txt)\n",
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