Skip to content

Game theoretic decision making for physical autonomous vehicles with pedestrian encounter at road crossing-scenario based on sequential chicken model.

Notifications You must be signed in to change notification settings

Rak-r/Game_Theory

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

16 Commits
 
 
 
 
 
 

Repository files navigation

This repository explores the operations with Game Theory for decision making. I have been researching about different ways to integrate sequential games for decision making into robotics.

Current Work

  1. Currently the game thepry experiments have been conducted using the existing Nashpy library with refrecne to previous work carrried in https://www.semanticscholar.org/paper/When-Should-the-Chicken-Cross-the-Road-Game-Theory-Fox-Camara/db03667574a7abfdbab1656ce803352bc57c874d

  2. The concept of Game theory integration is based on the strong fact that it provides probabilistic outcomes instead of pure outcomes which is importamt in Autonomous driving research with interaction in real world.

  3. The experiments have been performed with the Open source Hardware & Software platform named OpenPodCar_2 which is the upgraded version of predecessor.

The research focus on the integration of Pedestrian psychological behaviour into robot/autonomous vehicle control algorithms by providing the decison making ability which consist of the behavioural information. The current work is one of the (early/very few) research exprimentation and study on real physical vehcile.

Integrating ROS2 and Gambit

Gambit is more extensive library to conduct more accurate game theory related work. Extending the existing work to Gambut based system is one of the future tasks at the moment.

I provide some insights of using Gambit and ROS2 at veyr simple level along with some game theory concepts.

  1. The script Test_Game_Theory_ROS2.py includes a simple game similar to Prisonor's Dilemma created using gambit.

  2. To test the gambit connection with ROS2 Twist commands, a simple payoff outputs are assigned only to linear.x field.

  3. To test the working with Gazebo Garden / ignition Fortress, we can create a ros_gz_bridge with the following command.

    • ign gazebo ackermann_steering.sdf or gz sim ackermann_steering.sdf
    • ros2 run ros_gz_bridge parameter_bridge /model/vehicle_blue/cmd_vel@geometry_msgs/msg/Twist]gz.msgs.Twist.
    • In the new terminal : python3 Test_Game_theory_ROS2.py
  4. In the terminal, check ros2 topic list to check the published topic.

  5. We can visualise the robot moving with the output of the game's payoff.

Note: This script shows an initial insights to integrate game outputs with ROS2 and testing in simulation. In future more in-depth exploration will be provided.

About

Game theoretic decision making for physical autonomous vehicles with pedestrian encounter at road crossing-scenario based on sequential chicken model.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published