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sob_layer package from sob_layer repo

sob_layer

Package Summary

Tags No category tags.
Version 0.1.1
License MIT
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/dorezyuk/sob_layer.git
VCS Type git
VCS Version master
Last Updated 2021-11-22
Dev Status MAINTAINED
CI status
Released RELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

Plugin-replacement for the default costmap_2d::InflationLayer.

Additional Links

No additional links.

Maintainers

  • Dima Dorezyuk

Authors

No additional authors.

Small-Objects-Big (Sob) Layer

Build Status

The SobLayer offers a (likely) faster alternative to the commonly used costmap_2d::InflationLayer. It implements the distance transform algorithm described by Felzenszwalb and Huttenlocher [1].

Install/Build

If you’re using ros-noetic, you can install the package via apt:

sudo apt install ros-noetic-sob-layer

If you’re using an older ros-version or if you want to build the package from sources, follow the “normal” build process for catkin-based packages:

cd ~/catkin_ws/src
git clone https://github.com/dorezyuk/sob_layer.git
catkin build sob_layer --no-deps --cmake-args -DCMAKE_BUILD_TYPE=Release

You will get an additional performance boost by compiling with O3 optimization, which enables auto-vectorization:

catkin build sob_layer --no-deps --cmake-args -DCMAKE_BUILD_TYPE=Release -DCMAKE_CXX_FLAGS="-O3 -march=native"

The library offers also a benchmark-target. The benchmarking should help you to figure out, if the SobLayer offers a reasonable improvement over the costmap_2d::InflationLayer for your specific usecase/platform. The benchmark-target requires the benchmark library. If you want to build it, add -Dsob_layer_BENCHMARK=ON to your build command:

catkin build sob_layer --no-deps --cmake-args -DCMAKE_BUILD_TYPE=Release -Dsob_layer_BENCHMARK=ON

Requirements

The library requires at least C++11. It has been tested on Ubuntu 18.04 and Ubuntu 20.04 running ros-melodic and ros-noetic, respectively. Following compilers are known to work

  • GCC 7.5.0
  • Clang 6.0.0

Benchmarks

This library was benchmarked against the costmap_2d::InflationLayer. The benchmarks focus on two extreme scenarios.

In the first scenario we measure the performance of large, connected obstacles. We place a filled square in the middle of the map. The square is set to the size NxN. N ranges from 0 to 0.9 times the overall map’s edge E (assuming the map is a square with the size ExE). An increasing N increases hence the “load-factor” (number of occupied cells).

In the second scenario we measure the performance of unconnected obstacles. On an flattened map, we mark every N-th cell as occupied. With decreasing values for N, more cells are marked as occupied - our “load-factor” increases. The used N-values are [101, 51, 41, 31, 21, 11, 6, 3, 2].

image

The image above shows the results. The results were obtained on a AMD Ryzen 5 PRO 4650U CPU. The library was compiled with GCC 7.5.0 and “-O3 -march=native” flags.

The y-axis indicates the cpu-time. The x-axis shows the “load-factor” (increasing from left to right). Both scenarios were run for two map-sizes: 100x100 and 1000x1000. The upper row shows the results for the smaller size, the lower for the larger.

Config

The SobLayer follows mostly the configuration from costmap_2d::InflationLayer, easing the change for users.

# in your <common|local|global>_costmap.yaml
plugins:
    # ...
    -{name: inflation_layer,  type: "sob_layer::SobLayer"}

inflation_layer:
    # in meters. positive will suppress the automatic calculation from the
    # footprint
    inflation_radius: -1.
    # in meters, as in costmap_2d::InflationLayer
    inscribed_radius:  1.
    # decay, as in costmap_2d::InflationLayer
    cost_scaling_factor: 0
    # same behavior as in every costmap_2d::Layer:
    # calls to updateCosts and updateBounds will be skipped, if false
    enabled: true
    # If set to true, the costs with the value costmap_2d::NO_INFORMATION will
    # be overwritten by any cost larger than costmap_2d::FREE_SPACE.
    inflate_unknown: true


References

[1] Felzenszwalb, P., & Huttenlocher, D. (2012). Distance Transforms of Sampled Functions Theory of Computing, 8(19), 415–428.

CHANGELOG

Changelog for package sob_layer

0.1.1 (2021-11-22)

  • fix segmentation fault (#12)
  • Dima/unknown cost (#11)
  • Merge pull request #10 from dorezyuk/dima/dev2 Dima/dev2
  • update the image generation and images
  • adjust doc-string
  • move the power computation outside of the parabola loop
  • cache-friendlier formulation
  • fix compiler warnings when compiling with pedantic
  • remove calls to std::sqrt
  • fix include order
  • more explicit skipping
  • fix missing updateBounds call
  • Merge pull request #9 from dorezyuk/dima/dev misc fixes
  • misc fixes
  • Merge pull request #8 from dorezyuk/dima/dev Dima/dev
  • update README
  • fix cmake
  • Contributors: Dima Dorezyuk

0.1.0 (2020-11-24)

  • prepare for debian-packaging
  • minor fixes
  • adjust documentation
  • move the computeCache call into updateBounds
  • add documentation about unknown costs
  • add warning for unsupported parameters
  • fix doc
  • misc
  • Update README.md
  • add travis.yaml
  • add doc
  • add documentation and licence
  • Create LICENSE
  • init
  • Contributors: Dima Dorezyuk

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

No known dependants.

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

Recent questions tagged sob_layer at Robotics Stack Exchange

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