================================= patrolling_sim v2.2.4 (Jan. 2022) =================================

patrolling_sim for ROS (Noetic) – catkin version

Instalation instructions for Noetic version:

• For the ROS Noetic version to work it needs to use a modified version of stage_ros. Please clone this repo into your catkin workspace and compile it again.

Authors:

Main framework and basic algorithms:

• David Portugal (2011-2014), Luca Iocchi (2014-2016)

Additional algorithms:

• DTAP: Alessandro Farinelli (2014)

ROS Noetic migration:

• João Pedro Castilho (2022)

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patrolling_sim v2.2.2 (Dec. 2016)

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patrolling_sim for ROS (Groovy/Hydro/Indigo) – catkin version

Authors:

Main framework and basic algorithms: David Portugal (2011-2014), Luca Iocchi (2014-2016)

Additional algorithms:

• DTAP: Alessandro Farinelli (2014)

** NOTE ** Fork https://github.com/gennari/patrolling_sim implements a distributed execution of the patrolling environment that can be used also on real robots. These two branches will be merged soon.

This package contains the implementation of several algorithms for multi-robot patrolling and a general structure of a PatrolAgent that can be extended to implement other ones. It extends previous version of patrolling_sim with an improved structure of the code that allows easy integration of new algorithms, an improved navigation configuration that allows the robots to move at 1 m/s and to avoid most of conflicting situations, and a better management of the experiments and generation of the results.

The software is released as a ROS catkin package and requires the navigation stack (e.g., ros-indigo-navigation). For a quick try, just compile the workspace (‘catkin_make’), start the script ‘./start_experiment.py’, make your choices and see the experiment running.

WARNING: sometimes (on some machines) the very first run does not work, because of timing problems with roscore. Either restart the experiment a second time, or run roscore once before starting the experiment.

Several maps are available in the ‘maps’ folder. For map X the patrol graph is visible in the file maps/X/X-graph.png

Several algorithms have been implemented in the ‘src’ folder. Each method is implemented through a class ‘X_Agent’ that inherits from the abstract class ‘PatrolAgent’ many common services and functions.

Results of the experiments are stored in the ‘results’ folder.

In order to run a particular experiment or a set of experiments, use the run-exp.sh script template. It is convenient to copy this file in a new file that you can edit as you wish. For example, the current version of run_exp.sh allows to run an experiment for DISlabs, with 8 robots, 30 minutes, using DTAP algorithm, and other standard parameters. After 30 minutes the experiment terminates and the results will be available in the files results/{map}_{n.robots}/{algorithm}/{machine}/{date}*

The following result files are produced:

1) info.csv - contains a summary of the results of the experiment in a CSV format with the following values:

Map ; N. robots ; Goal wait time ; Communication delay ; Navigation module ; MRP Algorithm ; MRP Algorithm parameters ; Machine ; Date ; Sim Time ; Real time ; Interferences ; Termination status ; Idleness min ; avg ; stddev ; max ; Interference rate ; Total visits ; Avg visit per node ; Complete patrol cycles

2) results.txt - contains some information about the evolution of results in a text format

3) idleness.csv - contains the following results in a CSV format

Time ; Robot ; Node ; Node Idleness ; Interferences

4) timeresults.csv - contains evolution over time of the following results in a CSV format

Time ; Idleness min ; avg ; stddev ; max ; Interferences

The script can be extended to run multiple experiments in a single session, by just adding new commands like the one in the examples (possibly with different parameters).

** NEW NAVIGATION MODULES **

Default navigation modules are standard ROS nodes amcl (localization) and move_base (path planning and motion control). They work (usually) fine, but they require many computational resources that may limit the simulation of many robots in a single machine.

New navigation modules, called spqrel_navigation, are available at https://github.com/LCAS/spqrel_navigation/wiki. The localizer and the planner have the same interface as amcl and move_base so they can be used in their replacement by just changing the launch file. To install spqrel_navigation, follow instructions in the web site.

The spqrel_navigation modules have been fully integrated in patrolling_sim. Just select spqrel_navigation instead of ros as navigation module either in the start_experiment.py GUI or in the run_exp.sh script.

** NEW SUPPORT FOR EXTENDED STAGE API **

NOTE: Extended API for stage are available with customized versions of stage and stageros. (See https://github.com/iocchi/stage_ros for details).

With the use of the extended API it is possible to control activation of some GUI elements in Stage (e.g., footprints, simulation speedup, and screenshots). Set the Custom Stage flag to true in run_exp.sh script to activate these functions.