This package provides an implementation of a Full Coverage Path Planner (FCPP) using the Backtracking Spiral Algorithm (BSA), see [1].
This packages acts as a global planner plugin to the Move Base package (http://wiki.ros.org/move_base).
The user can configure robot radius and tool radius separately:
Keywords: coverage path planning, move base
Apache 2.0
Author(s): Yury Brodskiy, Ferry Schoenmakers, Tim Clephas, Jerrel Unkel, Loy van Beek, Cesar lopez
Maintainer: Cesar Lopez, cesar.lopez@nobleo.nl
Affiliation: Nobleo Projects BV, Eindhoven, the Netherlands
The Full Coverage Path Planner package has been tested under ROS Melodic and Ubuntu 18.04.
To build from source, clone the latest version from this repository into your workspace and compile the package using
cd catkin_workspace/src
git clone https://github.com/nobleo/full_coverage_path_planner.git
cd ../
catkin_make
All tests can be run using:
catkin build full_coverage_path_planner --catkin-make-args run_tests
Unit test that checks the basic functions used by the repository
Unit test that checks the basis spiral algorithm for full coverage. The test is performed for different situations to check that the algorithm coverage the accessible map cells. A test is also performed in randomly generated maps.
ROS system test that checks the full coverage path planner together with a tracking pid. A simulation is run such that a robot moves to fully cover the accessible cells in a given map.
Run a full navigation example using:
roslaunch full_coverage_path_planner test_full_coverage_path_planner.launch
Give a 2D-goal in rviz to start path planning algorithm
Depends on:
mobile_robot_simulator that integrates /cmd_vel into a base_link TF-frame and an odometry publisher
tracking_pid Global path tracking controller
Runs the full_coverage_path_planner global planner in combination with tracking PID local planner. Moreover a coverage progress tracking node is launched to monitor the coverage progress. Mobile_robot_simulator is used to integrate cmd_vel output into TF and odometry.
Arguments:
map
: path to a global costmap. Default: $(find full_coverage_path_planner)/maps/basement.yaml)
target_x_vel
: target x velocity for use in interpolator. Default: 0.2
target_yaw_vel
: target yaw velocity for use in interpolator. Default: 0.2
robot_radius
: radius of the robot for use in the global planner. Default: 0.6
tool_radius
: radius of the tool for use in the global planner. Default: 0.2
Start planning and tracking by giving a 2D nav goal.
The CoverageProgressNode keeps track of coverage progress. It does this by periodically looking up the position of the coverage disk in an occupancy grid. Cells within a radius from this position are 'covered'
/tf
([tf2_msgs/TFMessage])
ros tf dynamic transformations
/tf_static
([tf2_msgs/TFMessage])
ros tf static transformations
/coverage_grid
([nav_msgs/OccupancyGrid])
occupancy grid to visualize coverage progress
/coverage_progress
([std_msgs/Float32])
monitors coverage (from 0 none to 1 full) on the given area
/coverage_progress/reset
([std_srvs/SetBool])
resets coverage_progress node. For instance when robot position needs to be manually updatedtarget_area/x
: size in x of the target area to monitortarget_area/y
: size in y of the target area to monitorcoverage_radius
: radius of the tool to compute coverage progressFor use in move_base(_flex) as "base_global_planner"="full_coverage_path_planner/SpiralSTC". It uses global_cost_map and global_costmap/robot_radius.
robot_radius
: robot radius, which is used by the CPP algorithm to check for collisions with static maptool_radius
: tool radius, which is used by the CPP algorithm to discretize the space and find a full coverage plan[1] GONZALEZ, Enrique, et al. BSA: A complete coverage algorithm. In: Proceedings of the 2005 IEEE International Conference on Robotics and Automation. IEEE, 2005. p. 2040-2044.
Please report bugs and request features using the Issue Tracker.
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Supported by ROSIN - ROS-Industrial Quality-Assured Robot Software Components. More information: rosin-project.eu
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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 732287.