An Object-oriented approach to Robotic planning using Taxi domain

TL;DR

This paper presents an object-oriented Markov Decision Process approach for robotic planning and navigation in indoor environments, extending the Taxi domain to robotics with simulation and real robot implementation.

Contribution

It introduces an OO-MDP framework for robot navigation, adapting the Taxi domain to complex indoor environments with simulation in ROS and Gazebo.

Findings

Successful implementation of OO-MDP for robot navigation

Effective SLAM using 2D LIDAR in unknown environments

Potential for extension to various mobile and manipulative robots

Abstract

This paper aims to implement Object-Oriented Markov Decision Process (OO-MDPs) for goal planning and navigation of robot in an indoor environment. We use the OO-MDP representation of the environment which is a natural way of modeling the environment based on objects and their interactions. The paper aims to extend the well known Taxi domain example which has been tested on grid world environment to robotics domain with larger state-spaces. For the purpose of this project we have created simulation of the environment and robot in ROS with Gazebo and Rviz as visualization tools.The mobile robot uses a 2D LIDAR module to perform SLAM in the unknown environment. The goal of this project is to be able to make an autonomous agent capable of performing planning and navigation in an indoor environment to deliver boxes (passengers in Taxi domain) placed at random locations to a particular location (warehouse). The approach can be extended to a wide variety of mobile and manipulative robots