Package Summary

Tags No category tags.
Version 0.1.5
License BSD
Build type AMENT_CMAKE
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/ros-planning/navigation2.git
VCS Type git
VCS Version crystal-devel
Last Updated 2019-02-12
Dev Status MAINTAINED
Released RELEASED

Package Description

The costmap_queue package

Additional Links

No additional links.

Maintainers

  • David V. Lu!!

Authors

No additional authors.
README
No README found. See repository README.
CHANGELOG
No CHANGELOG found.

Wiki Tutorials

See ROS Wiki Tutorials for more details.

Source Tutorials

Not currently indexed.

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

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Recent questions tagged costmap_queue at answers.ros.org

No version for distro bouncy. Known supported distros are highlighted in the buttons above.

Package Summary

Tags No category tags.
Version 0.2.5
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/locusrobotics/robot_navigation.git
VCS Type git
VCS Version tf2
Last Updated 2019-02-12
Dev Status DEVELOPED
Released RELEASED

Package Description

Tool for iterating through the cells of a costmap to find the closest distance to a subset of cells.

Additional Links

No additional links.

Maintainers

  • David V. Lu!!

Authors

No additional authors.

costmap_queue

This package contains helper classes that implement one particular common costmap operation: figuring out the distance of every cell to a subset of those cells.

Inflation Example

Let's assume you have a grid G and you know that there are lethal obstacles in a subset of those cells O. You want to mark all cells within distance r with one value, and all cells within a greater distance r2 with another.

One costly way to do this would be to to iterate through all the cells g in G, calculate the distance from g to each cell in O, find the minimum distance, and compare to r and r2. This is roughly quadratic with the number of cells.

The more efficient way to do it is to start with all the cells in O in a queue. For each cell you dequeue, you calculate the distance to its origin cell from O and then enqueue all of its neighbors. This approach is roughly linear with the number of cells, although you need to be careful to not incur too many costs from resorting the queue.

Map Based Queue

While this operation could be done with the standard priority queue implementation, it can be optimized by using a custom priority queue based on std::map. This relies on the fact that many of the items inserted into the queue will have the same priority. In the costmap_queue, the priorities used are distances on the grid, of which there are a finite number. Thus by grouping all of the elements of the same weight into a vector together, and storing them in the std::map with their priority, we can eliminate the need to resort after each individual item is popped. This is based on the optimizations to the Inflation algorithm.

Also, since the same (or similar) distances will be used in the costmap_queue from iteration to iteration, additional time can be saved by not destroying the vectors in the map, and reusing them iteration to iteration.

Costmap Queue

The CostmapQueue class operates on a nav_core2::Costmap. First, you must enqueue all of the "subset" of cells (i.e. O in the above example) using enqueueCell. Then, while the queue is not empty (i.e. isEmpty is false), you can call costmap_queue::CellData cell = q.getNextCell(); to get the next cell in the queue.

The CellData class contains 5 values: x_ and y_ are the coordinates for the current cell, src_x_ and src_y_ are the coordinates for the original cell, and distance_ is the distance between them.

By default, CostmapQueue will iterate through all the cells in the Costmap. If you want to limit it to only cells within a certain distance, you can use LimitedCostmapQueue instead.

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

See ROS Wiki Tutorials for more details.

Source Tutorials

Not currently indexed.

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged costmap_queue at answers.ros.org

Package Summary

Tags No category tags.
Version 0.2.5
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/locusrobotics/robot_navigation.git
VCS Type git
VCS Version master
Last Updated 2019-02-12
Dev Status DEVELOPED
Released RELEASED

Package Description

Tool for iterating through the cells of a costmap to find the closest distance to a subset of cells.

Additional Links

No additional links.

Maintainers

  • David V. Lu!!

Authors

No additional authors.

costmap_queue

This package contains helper classes that implement one particular common costmap operation: figuring out the distance of every cell to a subset of those cells.

Inflation Example

Let's assume you have a grid G and you know that there are lethal obstacles in a subset of those cells O. You want to mark all cells within distance r with one value, and all cells within a greater distance r2 with another.

One costly way to do this would be to to iterate through all the cells g in G, calculate the distance from g to each cell in O, find the minimum distance, and compare to r and r2. This is roughly quadratic with the number of cells.

The more efficient way to do it is to start with all the cells in O in a queue. For each cell you dequeue, you calculate the distance to its origin cell from O and then enqueue all of its neighbors. This approach is roughly linear with the number of cells, although you need to be careful to not incur too many costs from resorting the queue.

Map Based Queue

While this operation could be done with the standard priority queue implementation, it can be optimized by using a custom priority queue based on std::map. This relies on the fact that many of the items inserted into the queue will have the same priority. In the costmap_queue, the priorities used are distances on the grid, of which there are a finite number. Thus by grouping all of the elements of the same weight into a vector together, and storing them in the std::map with their priority, we can eliminate the need to resort after each individual item is popped. This is based on the optimizations to the Inflation algorithm.

Also, since the same (or similar) distances will be used in the costmap_queue from iteration to iteration, additional time can be saved by not destroying the vectors in the map, and reusing them iteration to iteration.

Costmap Queue

The CostmapQueue class operates on a nav_core2::Costmap. First, you must enqueue all of the "subset" of cells (i.e. O in the above example) using enqueueCell. Then, while the queue is not empty (i.e. isEmpty is false), you can call costmap_queue::CellData cell = q.getNextCell(); to get the next cell in the queue.

The CellData class contains 5 values: x_ and y_ are the coordinates for the current cell, src_x_ and src_y_ are the coordinates for the original cell, and distance_ is the distance between them.

By default, CostmapQueue will iterate through all the cells in the Costmap. If you want to limit it to only cells within a certain distance, you can use LimitedCostmapQueue instead.

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

See ROS Wiki Tutorials for more details.

Source Tutorials

Not currently indexed.

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged costmap_queue at answers.ros.org

Package Summary

Tags No category tags.
Version 0.2.5
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/locusrobotics/robot_navigation.git
VCS Type git
VCS Version master
Last Updated 2019-02-12
Dev Status DEVELOPED
Released RELEASED

Package Description

Tool for iterating through the cells of a costmap to find the closest distance to a subset of cells.

Additional Links

No additional links.

Maintainers

  • David V. Lu!!

Authors

No additional authors.

costmap_queue

This package contains helper classes that implement one particular common costmap operation: figuring out the distance of every cell to a subset of those cells.

Inflation Example

Let's assume you have a grid G and you know that there are lethal obstacles in a subset of those cells O. You want to mark all cells within distance r with one value, and all cells within a greater distance r2 with another.

One costly way to do this would be to to iterate through all the cells g in G, calculate the distance from g to each cell in O, find the minimum distance, and compare to r and r2. This is roughly quadratic with the number of cells.

The more efficient way to do it is to start with all the cells in O in a queue. For each cell you dequeue, you calculate the distance to its origin cell from O and then enqueue all of its neighbors. This approach is roughly linear with the number of cells, although you need to be careful to not incur too many costs from resorting the queue.

Map Based Queue

While this operation could be done with the standard priority queue implementation, it can be optimized by using a custom priority queue based on std::map. This relies on the fact that many of the items inserted into the queue will have the same priority. In the costmap_queue, the priorities used are distances on the grid, of which there are a finite number. Thus by grouping all of the elements of the same weight into a vector together, and storing them in the std::map with their priority, we can eliminate the need to resort after each individual item is popped. This is based on the optimizations to the Inflation algorithm.

Also, since the same (or similar) distances will be used in the costmap_queue from iteration to iteration, additional time can be saved by not destroying the vectors in the map, and reusing them iteration to iteration.

Costmap Queue

The CostmapQueue class operates on a nav_core2::Costmap. First, you must enqueue all of the "subset" of cells (i.e. O in the above example) using enqueueCell. Then, while the queue is not empty (i.e. isEmpty is false), you can call costmap_queue::CellData cell = q.getNextCell(); to get the next cell in the queue.

The CellData class contains 5 values: x_ and y_ are the coordinates for the current cell, src_x_ and src_y_ are the coordinates for the original cell, and distance_ is the distance between them.

By default, CostmapQueue will iterate through all the cells in the Costmap. If you want to limit it to only cells within a certain distance, you can use LimitedCostmapQueue instead.

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

See ROS Wiki Tutorials for more details.

Source Tutorials

Not currently indexed.

Package Dependencies

System Dependencies

No direct system dependencies.

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged costmap_queue at answers.ros.org

Package Summary

Tags No category tags.
Version 0.2.5
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/locusrobotics/robot_navigation.git
VCS Type git
VCS Version master
Last Updated 2019-02-12
Dev Status DEVELOPED
Released RELEASED

Package Description

Tool for iterating through the cells of a costmap to find the closest distance to a subset of cells.

Additional Links

No additional links.

Maintainers

  • David V. Lu!!

Authors

No additional authors.

costmap_queue

This package contains helper classes that implement one particular common costmap operation: figuring out the distance of every cell to a subset of those cells.

Inflation Example

Let's assume you have a grid G and you know that there are lethal obstacles in a subset of those cells O. You want to mark all cells within distance r with one value, and all cells within a greater distance r2 with another.

One costly way to do this would be to to iterate through all the cells g in G, calculate the distance from g to each cell in O, find the minimum distance, and compare to r and r2. This is roughly quadratic with the number of cells.

The more efficient way to do it is to start with all the cells in O in a queue. For each cell you dequeue, you calculate the distance to its origin cell from O and then enqueue all of its neighbors. This approach is roughly linear with the number of cells, although you need to be careful to not incur too many costs from resorting the queue.

Map Based Queue

While this operation could be done with the standard priority queue implementation, it can be optimized by using a custom priority queue based on std::map. This relies on the fact that many of the items inserted into the queue will have the same priority. In the costmap_queue, the priorities used are distances on the grid, of which there are a finite number. Thus by grouping all of the elements of the same weight into a vector together, and storing them in the std::map with their priority, we can eliminate the need to resort after each individual item is popped. This is based on the optimizations to the Inflation algorithm.

Also, since the same (or similar) distances will be used in the costmap_queue from iteration to iteration, additional time can be saved by not destroying the vectors in the map, and reusing them iteration to iteration.

Costmap Queue

The CostmapQueue class operates on a nav_core2::Costmap. First, you must enqueue all of the "subset" of cells (i.e. O in the above example) using enqueueCell. Then, while the queue is not empty (i.e. isEmpty is false), you can call costmap_queue::CellData cell = q.getNextCell(); to get the next cell in the queue.

The CellData class contains 5 values: x_ and y_ are the coordinates for the current cell, src_x_ and src_y_ are the coordinates for the original cell, and distance_ is the distance between them.

By default, CostmapQueue will iterate through all the cells in the Costmap. If you want to limit it to only cells within a certain distance, you can use LimitedCostmapQueue instead.

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

See ROS Wiki Tutorials for more details.

Source Tutorials

Not currently indexed.

Package Dependencies

System Dependencies

No direct system dependencies.

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged costmap_queue at answers.ros.org

No version for distro ardent. Known supported distros are highlighted in the buttons above.
No version for distro jade. Known supported distros are highlighted in the buttons above.
No version for distro hydro. Known supported distros are highlighted in the buttons above.