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‎README.md‎

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@@ -7,7 +7,7 @@ The library provides a simulation environment, algorithms, and GNN-based archite
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<img align="right" width="300" src="https://github.com/KumarRobotics/CoverageControl/raw/main/doc/graphics/LPAC.gif">
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**Key features:**
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- The core library `CoverageControlCore` is written in `C++` and `CUDA` to handle large-scale simulations
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- The core library is written in `C++` and `CUDA` to handle large-scale simulations
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- There are `python` bindings that interface with the core library
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- Several Centroidal Voronoi Tessellation (CVT)-based algorithms (aka Lloyd's algorithms)
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- Learnable Perception-Action-Communication (LPAC) architecture for the coverage control problem is implemented in `PyTorch` and `PyTorch Geometric`
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pip install coverage_control
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```
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See the [Quick Start](https://kumarrobotics.github.io/CoverageControl/quick_start.html) guide for a quick introduction to the library.
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See [Installation](https://kumarrobotics.github.io/CoverageControl/installation.html) for more details on installation.
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See [Quick Start](https://kumarrobotics.github.io/CoverageControl/quick_start.html) guide for a quick introduction to the library.
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---
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‎cppsrc/core/include/CoverageControl/cgal/polygon_utils.h‎

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*
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* @param[in] num_polygons The number of polygons to generate
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* @param[in] max_vertices The maximum number of vertices in each polygon
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* @param[bounding_box_lower] The lower left corner of the bounding box
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* @param[bounding_box_upper] The upper right corner of the bounding box
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* @param[radius] The radius of the circle in which the polygons are generated
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* @param[in] half_width The half-width of the polygon
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* @param[in] world_size The size of the world
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* @param[out] polygons The output polygons
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*/
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‎doc/config/custom.css‎

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text-align: right;
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}
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#nav-tree a:focus {
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outline-style: none;
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}
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/* #nav-tree a:focus { */
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/* outline-style: none; */
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/* } */
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#nav-tree .selected .arrow {
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opacity: var(--side-nav-arrow-hover-opacity)
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}
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/* #nav-tree .selected .arrow { */
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/* opacity: var(--side-nav-arrow-hover-opacity) */
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/* } */
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#nav-tree a:focus .arrow {
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font-size: 60%;

‎doc/config/doxygen-awesome.css‎

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a:link, a:visited, a:hover, a:focus, a:active {
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color: var(--primary-color) !important;
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font-weight: 500;
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background: none;
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}
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a.anchor {
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line-height: var(--tree-item-height);
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#nav-tree .item > a:focus {
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outline: none;
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}
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#nav-sync {
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bottom: 12px;
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right: 12px;
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#nav-tree .arrow {
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‎doc/manual/README.md‎

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The library provides a simulation environment, algorithms, and GNN-based architectures for the coverage control problem.
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**Key features:**
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- The core library `CoverageControlCore` is written in `C++` and `CUDA` to handle large-scale simulations
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- The core library is written in `C++` and `CUDA` to handle large-scale simulations
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- There are `python` bindings that interface with the core library
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- Several Centroidal Voronoi Tessellation (CVT)-based algorithms (aka Lloyd's algorithms)
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- Learnable Perception-Action-Communication (LPAC) architecture for the coverage control problem is implemented in `PyTorch` and `PyTorch Geometric`
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pip install coverage_control
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```
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See the [Quick Start](quick_start.md) guide for a quick introduction to the library.
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See [Installation](https://kumarrobotics.github.io/CoverageControl/installation.html) for more details on installation.
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See [Quick Start](https://kumarrobotics.github.io/CoverageControl/quick_start.html) guide for a quick introduction to the library.
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‎doc/manual/docker.md‎

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|Tags Suffix | Flags|
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|--- | ---|
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|`python2.2.1-cuda12.3.1-ros2humble` | `--with-ros --with-cuda`|
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|`python2.2.1-cuda12.3.1` | `--with-cuda`|
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|`python2.2.1-ros2humble` | `--with-ros`|
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|`python2.2.1` | None|
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|`python2.2.2-cuda12.2.2-ros2humble` | `--with-ros --with-cuda`|
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|`python2.2.2-cuda12.2.2` | `--with-cuda`|
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|`python2.2.2-ros2humble` | `--with-ros`|
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|`python2.2.2` | None|
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--------
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‎doc/manual/installation.md‎

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pip install coverage_control
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```
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The package depends on the following packages, which are installed as dependencies:
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The package depends on the following packages
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- [PyTorch](https://pytorch.org/)
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- [PyTorch Geometric](https://pytorch-geometric.readthedocs.io/en/latest/)
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```bash
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pip install torch torchvision torch-geometric
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```
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\note PyTorch and PyTorch Geometric have CPU and CUDA-specific versions. The package installs the default version (latest CUDA).
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\note PyTorch and PyTorch Geometric have CPU and CUDA-specific versions. The command installs the default version (latest CUDA).
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We need the following optional packages for visualization and video generation:
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- `gnuplot` or `gnuplot-nox` (for visualizing environment)
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## Docker Container
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Container can be created using the script in `setup_utils/create_container.sh`.
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cd ${CoverageControl_ws}/src/CoverageControl/setup_utils
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cd ${CoverageControl_ws}/src/CoverageControl/setup_utils/docker
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bash create_container.sh --with-cuda -d ${CoverageControl_ws} # See flags below
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```
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|Tags Suffix | Flags|
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|--- | ---|
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|`python2.2.1-cuda12.3.1-ros2humble` | `--with-ros --with-cuda`|
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|`python2.2.1-cuda12.3.1` | `--with-cuda`|
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|`python2.2.2-cuda12.2.2-ros2humble` | `--with-ros --with-cuda`|
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|`python2.2.2-cuda12.2.2` | `--with-cuda`|
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|`python2.2.1-ros2humble` | `--with-ros`|
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|`python2.2.1` | None|
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|`python2.2.2` | None|
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The library is already built and installed in the container.
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However, if you want to build it again, you can do so following the [Installation from Source](#installation-from-source) instructions (except for the prerequisites).
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## Building the Core C++ Library
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\note This is only necessary if you want to use the C++ library directly.
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We will organize files in a **workspace** directory: `${CoverageControl_ws}` (e.g., ~/CoverageControl\_ws).
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‎doc/manual/lpac.md‎

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```bash
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${CoverageControl_ws}/lpac/params/eval_single.toml
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${CoverageControl_ws}/lpac/params/eval_single_env.toml
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```
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The `eval.toml` and `eval_single.toml` files are also provided in the `params` directory of the repository.

‎doc/manual/quick_start.md‎

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# C++ Interface
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\note The C++ interface is not available in the pip package. You need to build the library from source. See the [Installation](https://kumarrobotics.github.io/CoverageControl/installation.html#installation-from-source) guide for instructions.
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Include the `CoverageControl` library, algorithms, and other necessary headers:
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#include <CoverageControl/parameters.h>

‎params/coverage_control_params.toml‎

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NumRobots = 32
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NumFeatures = 32
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NumPolygons = 0
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MaxVertices = 10
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PolygonRadius = 64
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# Parameters for the environment
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[Environment]
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