https://github.com/bradleynull/drone-path-planning
C++ example for parsing maps and planning paths based on given drone parameters
https://github.com/bradleynull/drone-path-planning
cpp drone pathplanning robotics
Last synced: 3 months ago
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C++ example for parsing maps and planning paths based on given drone parameters
- Host: GitHub
- URL: https://github.com/bradleynull/drone-path-planning
- Owner: bradleynull
- Created: 2020-08-13T20:45:18.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2020-08-13T20:48:59.000Z (almost 5 years ago)
- Last Synced: 2025-01-26T18:25:11.402Z (4 months ago)
- Topics: cpp, drone, pathplanning, robotics
- Language: C++
- Homepage:
- Size: 184 KB
- Stars: 3
- Watchers: 3
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# drone-path-planning
Drone path planning exercise for debugging drone algorithms.
## Dependencies
This project uses standard C++ 14. To build you will need to install `cmake`:
* [CMake](https://cmake.org/download/)
## Build
```bash
$ cd ./drone-path-planning
$ mkdir ./build
$ cd ./build
$ cmake ..
```
### Building and running on Windows
The CMake project will generate a solution file you can use to debug in Visual
Studio or just open the folder with VS Code. To run tests:
```bash
$ ctest -C Debug
```
### Building and running on Linux
From the `build` directory
```bash
$ make test
```
### Analyzing Data
There is a test in the `path_planner_test.cc` named `filter_larger_path()` that
will apply several filters to the elevation profile output by the path planner.
The output is `filter_large_path.json` in the form:
```json
[
{
"name": ,
"path": [...]
},
...
]
```
There is also a small python script that produces plots for each of the paths
in file. The legend shows the `"name"` of each plot which consist of the
original elevation along the path and the above-ground-level elevation. Each
of the filter paths from the test are also shown:
There's an `environment.yml` file that can be used to install the dependencies
necessary for plotting the path. This can be installed using
[Miniconda](https://docs.conda.io/en/latest/miniconda.html):
```bash
$ conda env create -f ./environment.yml
```
To run the plotter from the root directory just:
```bash
$ python ./tests/plot_data.py --data ./filter_large_path.json
```