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Copy file name to clipboardexpand all lines: common/autoware_grid_map_utils/README.md
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## API
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The `grid_map_utils::PolygonIterator` follows the same API as the original [`grid_map::PolygonIterator`](https://docs.ros.org/en/kinetic/api/grid_map_core/html/classgrid__map_1_1PolygonIterator.html).
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The `autoware::grid_map_utils::PolygonIterator` follows the same API as the original [`grid_map::PolygonIterator`](https://docs.ros.org/en/kinetic/api/grid_map_core/html/classgrid__map_1_1PolygonIterator.html).
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## Assumptions
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The behavior of the `grid_map_utils::PolygonIterator` is only guaranteed to match the `grid_map::PolygonIterator` if edges of the polygon do not _exactly_ cross any cell center.
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The behavior of the `autoware::grid_map_utils::PolygonIterator` is only guaranteed to match the `grid_map::PolygonIterator` if edges of the polygon do not _exactly_ cross any cell center.
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In such a case, whether the crossed cell is considered inside or outside of the polygon can vary due to floating precision error.
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## Performances
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Benchmarking code is implemented in `test/benchmarking.cpp` and is also used to validate that the `grid_map_utils::PolygonIterator` behaves exactly like the `grid_map::PolygonIterator`.
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Benchmarking code is implemented in `test/benchmarking.cpp` and is also used to validate that the `autoware::grid_map_utils::PolygonIterator` behaves exactly like the `grid_map::PolygonIterator`.
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The following figure shows a comparison of the runtime between the implementation of this package (`grid_map_utils`) and the original implementation (`grid_map`).
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The following figure shows a comparison of the runtime between the implementation of this package (`autoware_grid_map_utils`) and the original implementation (`grid_map`).
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The time measured includes the construction of the iterator and the iteration over all indexes and is shown using a logarithmic scale.
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Results were obtained varying the side size of a square grid map with `100 <= n <= 1000` (size=`n` means a grid of `n x n` cells),
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random polygons with a number of vertices `3 <= m <= 100` and with each parameter `(n,m)` repeated 10 times.
Copy file name to clipboardexpand all lines: planning/motion_velocity_planner/autoware_motion_velocity_obstacle_velocity_limiter_module/README.md
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#### Occupancy Grid
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Masking is performed by iterating through the cells inside each polygon mask using the [`grid_map_utils::PolygonIterator`](https://github.com/autowarefoundation/autoware.universe/tree/main/common/grid_map_utils) function.
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Masking is performed by iterating through the cells inside each polygon mask using the [`autoware::grid_map_utils::PolygonIterator`](https://github.com/autowarefoundation/autoware.universe/tree/main/common/autoware_grid_map_utils) function.
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A threshold is then applied to only keep cells with an occupancy value above parameter `obstacles.occupancy_grid_threshold`.
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Finally, the image is converted to an image and obstacle linestrings are extracted using the opencv function
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