An Object-oriented approach to Robotic planning using Taxi domain
This work addresses planning and navigation for mobile robots in indoor settings, but it is incremental as it adapts an existing method to a new domain.
The paper tackles robotic planning in indoor environments by implementing Object-Oriented Markov Decision Processes (OO-MDPs) to extend the Taxi domain to robotics, resulting in a simulation using ROS, Gazebo, and Rviz for autonomous box delivery.
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