Assignment1 Survailence Robot

Documentation

1. Introduction

This github repository shows how to build a finit-state machine in ROS environment based on SMACH ros-package, and how to build a topological onotology of the wrold, in this small project, Protogé is used for building the ontology, ARMOR service is used for access and modify the ontology.

Environment

It is a 2D-environmen built up with 4 rooms R1 R2 R3 R4, 2 corridors C1 C2 and one special room E used as a waiting room befor filling the map, and a charging station as well. And 7 doors D1 ... D7

Senario

We have a survallience robot that moves in a 2D environment. First the robot waits in room E untill the whol map is loaded into the ontology, then the robot keeps moving between the corridors C1 and C2 for infinit time. The robot must go to the charging station E when its battery is low, otherwise he must visit the urgent rooms if any, then goes back to its normal behavior moving between cooridors.

Ontology

• Entity

• Individuals

  • C1 C2 E: Cooridors
  • R1 R2 R3 R4: Rooms
  • D1 D2 D3 D4 D5 D6 D7: Doors

• Object properties

  • isIn
  • canReach
  • hasDoor
  • connectedTo

• Data properties

  • Now
  • visitedAt
  • uregencyThreshold

  2. Discreption of software architecture

  

  The software architecture is buily up by four nodes, a list of parameters and two customized messages they are listed bellow. Each node has a specific task to do:

1. user_interface
2. state_machine
3. battery_controller
4. armor

• List of paramerters
• List of meesages

1- user_interface

This node interact with the user in an infinit loop, allows the user to access and modify the onotology by just entring some specific inputs, then this node call the armor server in the appropriate command. Also this node publish the state of the map in the topic /battery_state. It publishes 0 if it is not fully loaded and 1 if it is fully loaded.

• The required inputs are:
  • The type of operation manipulation, query, utils
  • The name of operation ADD, LOAD, ...
  • The primary_command_spec
  • The secondary_command_spec
  • The number of arguments
  • Arguments

2- state_machine

It controlls how the robot changes its state based on the reasoning of the topological ontology, and the battery state of the robot. This node subscribes to two topics /battery_state and /map_state, and it calls the armor server for updating the loaded ontology. The states of the robot are listed bellow.

• filling_map
• moving_in_corridors
• visiting_urgent

3- battery_controller

This is a publisher to the topic /baterry_state, it publishes different state of the battery TrueorFalse in a specific duration, the durations to be full or low are passed as parameters.

4- armor

The ARMOR package is an external package used to communicate with the Cluedo OWL ontology, it is a ROS wrapper that helps to make this communication possible. For more information about ARMOR click here

List of parameters

It is a yaml file that list all the parameters used in this project which are

• time_to_stay_in_location defeault value = 1 (s)
• time_of_one_charge defeault value = 30 (s)
• time_of_charging defeault value = 15 (s)
• visitedAt_R1 defeault value = 1665579740
• visitedAt_R2 defeault value = 1665579740
• visitedAt_R3 defeault value = 1665579740
• visitedAt_R4 defeault value = 1665579740
• visitedAt_C1 defeault value = 1665579740
• visitedAt_C2 defeault value = 1665579740
• visitedAt_E defeault value = 1665579740

List of messages

• Map_state.msg: int32 map_state, carry the state of the map

  • It is 1 if the map is fully loaded
  • It is 0 if the map is not fully loaded

• Battry_state.msg: int32 battery_state, carry the state of the battery

  • It is 1 if the battery is full
  • It is 0 if the battery is low

  There are four states in this state diagram, the task of each state is explained below:

1. MapLoading: The robots keeps waiting in room E untill the whole map is loaded, the robot can know if the map is fully loaded by subscribing to the topic /map_state. When the map is fully loaded the robot go to MOVING_IN_CORRIDORS state trough the transition move.
2. Normal: The robots keeps moving between C1 and C2 for infinit time, the robots keep cheking the state of the battery by subscribing to the topic /battery_state, if the battery is low the robot goes to CHARGING state trough the transition tired. if the battery is not low, the robot cheks if there is an urgent room by quering the individuals of the class urg. If there is an urgent room the robot goes to VISITING_URGENT state through the transition urgent.
3. Visiting_urgent: First, the robots checks if the battery is low goes to CHARGING state, else it checkes it the urgent room is reacheable by quering the object properties of the robot canReach, if the room can be reached it visit it and return back to the MOVING_IN_CORRIDORS trough the transition visited. If the urgent room is not reacheable it goes to MOVING_IN_CORRIDORS state through the transition not_reached, in this case the robot will change the corridors and visit it again.
4. Battery Low: The robot keeps checking the state of the battery, if it is full it goes to MOVING_IN_COORIDORS state the the transition charged, otherwise, it stays in the CHARGING state.

3. Instalation and running procedures

1. Clone the repository in your work_space git clone https://github.com/awaistahir29/survailence_robot.git
2. (optional!) Change the other parameters if you want to test some relevent parts of the code
3. If you do not have smach_package, run this command: sudo apt-get install ros-noetic-smach-ros
4. If you do not have armor installed, follow this git hub repository https://github.com/EmaroLab/armor_rds_tutorial.git
5. Open new terminal and run roslaunch assignment solution.launch

• When you run this command, three windows and the should pop-up

  1. user_interface.py
  2. state_machine.py
  3. battery.py
  • user_inerface.py: allows you to load the ontology, and notify the algorithm if the map is fully loaded
  • state_machine.py: prints the state transition of the robot, helps you to understand and debug
  • battery.py: allows you to monitor the state of the better
  • charging

  5. Working hypothesis and environement

In this project there are many assumptions made on the environement in order to make the project simpler, the assumptions are explained bellow

1. The movement of the robot is not performed in real world, so if we make a simulation we will not see the robot moving. The movements is performed only on the level of onotology. A movement is defined by changing the location of the robot by isIn, and updating the time now.
2. Initializing the visitedAt data proporty of a location to different values to avoid making all of them urgent at the same time
3. When a robot is in a specific location, it can reach only the locations that need one door transmition

Pssible Limitations

1. "The time to do a move" and "the time to stay in a location" and "the time step to be updated" is considered to be the same, and it is passed as a parameter to the code by the parameter time_to_stay_in_location
2. The robot does not move it there is a missing part in the map, this is not practical, because in real life if we have a person in the same situation, the persone starts moving and discouvering the environment by himself, and starts acting even if he does not know the whole environment

Possible improvements

1. The movement can be improved by consediring a real motion in cartesian space, this is can be done by including the planer and controller nodes in the architecture. for more information about planer and controller nodes visit this repository
2. The time can be continuously updated and depends on the distance and speed of the robot to reach a specific location
3. Make the robot willing to move by knowing just its current position and how he can reach another position and building the map by itself

7. Author and Teachers contacts

• Author
  • name: Awais Tahir
  • email: awaistahir29@gmail.com
• Teachers
  • name: Luca Buoncompagni luca.buoncompagni@edu.unige.it
  • name: Carmine Recchiuto carmine.recchiuto@dibris.unige.it