Robot Planning and Automated Planning Joint Project: Pursuer-Escaper Scenario

A pursuer evader scenario with borders and obstacles inthe map is a good case study to apply motion planning andautomated planning to a real problem. Here, the pursuer has to catch the evader before it reaches one of the gates. To do so, the planning node of a ROS environment is coded. The information obtained by the processing of the map is exploited to encode the problem structure into a graph and then to encode the problem in PDDL. Metric FF is used to obtain the path which will then be refined by an iterative dynamic programming solution of the Dubins problem. The system is able to handle increasing evader behavioural complexities by planning a "fake" path of the evader and encode the information in the pursuer planner.

Acknowledgment

This is a project for the courses: Robot Planning and Automated Planning of the University of Trento.

Professors:

• Luigi Palopoli
• Marco Roveri

Students:

• Giovanni Lorenzini
• Simone Luchetta
• Diego Planchenstainer

Used libraries and softwares:

• AlexRookie/AppliedRoboticsEnvironment
• AlexRookie/AppliedRoboticsStudentInterface
• Boost
• CDT
• Clipper
• Metric FF

Installation

Use Ubuntu 16.04 LTS.

Install the ROS

Setup:

$ sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main" > /etc/apt/sources.list.d/ros-latest.list'
$ sudo apt-key adv --keyserver 'hkp://keyserver.ubuntu.com:80' --recv-key C1CF6E31E6BADE8868B172B4F42ED6FBAB17C654
$ sudo apt-get update
$ sudo apt-get install ros-kinetic-desktop-full

Environment setup:

$ echo "source /opt/ros/kinetic/setup.bash" >> ~/.bashrc
$ source ~/.bashrc

Dependencies for building packages:

$ sudo apt install python-rosdep
$ sudo apt install ros-kinetic-rqt-multiplot ros-kinetic-usb-cam
$ sudo apt install python-rosinstall python-rosinstall-generator python-wstool build-essential
$ sudo apt-get install python-catkin-tools
$ sudo apt install chrpath
$ sudo apt-get install libignition-math2-dev
$ sudo apt install ros-kinetic-jsk-visualization

Initialize rosdep:

$ sudo rosdep init
$ rosdep update

Install Gazebo

Setup:

$ sudo sh -c 'echo "deb http://packages.osrfoundation.org/gazebo/ubuntu-stable `lsb_release -cs` main" > /etc/apt/sources.list.d/gazebo-stable.list'
$ wget https://packages.osrfoundation.org/gazebo.key -O - | sudo apt-key add -

Install Gazebo:

$ sudo apt-get update
$ sudo apt-get install gazebo7

Install OpenCV 3.3.1

Setup:

$ sudo apt-get update

Install dependencies:

$ sudo apt-get install cmake git libgtk2.0-dev pkg-config
$ sudo apt-get install -y qt5-default libvtk6-dev
$ sudo apt-get install -y zlib1g-dev libjpeg-dev libwebp-dev libpng-dev libtiff5-dev libjasper-dev libopenexr-dev libgdal-dev
$ sudo apt-get install -y libdc1394-22-dev libavcodec-dev libavformat-dev libswscale-dev libtheora-dev libvorbis-dev libxvidcore-dev libx264-dev yasm libopencore-amrnb-dev libopencore-amrwb-dev libv4l-dev libxine2-dev

Install the library:

$ wget https://github.com/opencv/opencv/archive/3.3.1.zip
$ unzip 3.3.1.zip
$ rm 3.3.1.zip
$ mv opencv-3.3.1 OpenCV
$ cd OpenCV
$ mkdir build
$ cd build
$ cmake -DWITH_QT=ON -DWITH_OPENGL=ON -DBUILD_EXAMPLES=ON ..
$ make -j4

Install OpenCV:

$ sudo make install
$ sudo ldconfig

Clone the simulator

Clone git:

$ mkdir ~/workspace
$ cd ~/workspace
$ git clone https://github.com/lorenzinigiovanni/AppliedRoboticsEnvironment simulator

Compile the simulator:

$ cd ~/workspace/simulator
$ catkin build
source ./environment.sh

Clone the project

Clone git:

$ cd ~/workspace
$ git clone https://github.com/lorenzinigiovanni/AppliedRoboticsStudentInterface project

Create build folder:

$ cd ~/workspace/project
$ mkdir build

Automatic source of the environment

Do this only if the above procedure worked without errors:

$ echo "source ${AR_CATKIN_ROOT}/environment.sh" >> ~/.bashrc
$ echo "source ${AR_ROOT}/environment.sh > /dev/null 2>&1" >> ~/.bashrc

Download Boost C++ library

$ cd ~/workspace/project/src
$ wget https://boostorg.jfrog.io/artifactory/main/release/1.77.0/source/boost_1_77_0.tar.gz
$ tar -xf boost_1_77_0.tar.gz
$ rm boost_1_77_0.tar.gz
$ mv boost_1_77_0 boost

Download and compile Metric FF

Download Metric FF:

$ cd ~
$ wget https://fai.cs.uni-saarland.de/hoffmann/ff/Metric-FF-v2.1.tgz
$ tar zxvf Metric-FF-v2.1.tgz
$ rm Metric-FF-v2.1.tgz
$ mv Metric-FF-v2.1 MetricFF

Compile Metric FF and copy it in the project folder:

$ sudo apt-get install build-essential flex bison
$ cd ~/MetricFF
$ make
$ cp ff ~/workspace/project/src/pddl

Preparation

Create a directory to store debug images (clean the content before each run):

$ mkdir ~/workspace/images

Create a directory to store the robots status (clean the content before each run):

$ mkdir ~/workspace/state

In the file settings.hpp, it is possible to set the following parameters:

• Behavioral complexity of the robot, value between 1 and 3;
• If to save plan image in workspace/images/ folder;
• Length of path the robot takes for a step;
• Offset value to be applied to borders and obstacles;
• Curvature parameter for the robot;
• The absolute path of the workspace folder used for the project.

$ nano ~/workspace/project/src/settings.hpp

Compile:

$ cd ~/workspace/project/build
$ cmake ..
$ make
$ source ../environment.sh

Alternatively, run prepare.sh (before each run):

$ cd ~/workspace/project
$ ./prepare.sh

Execution

Open three terminals.

In the first one run the simulator:

$ AR_simulator_gui 

In the second one run the pipeline:

$ AR_pipeline

In the third one make the robots move, repeat the command until the robots reach the goal:

$ AR_run