‍

Overview

The primary objective is to enable the mobile rover to autonomously traverse through its surroundings, reaching a predetermined destination while adeptly avoiding obstacles, all without human intervention. The project adopts two key approaches to achieve this goal: Simultaneous Localization and Mapping (SLAM)-based navigation and Q-Learning algorithm which is a Reinforcement  Learning (RL) approach.

The performance of the robot on both approaches is subsequently assessed within the confines of the simulated environment (Gazebo) to gauge its effectiveness and efficiency.

‍

View project documentation and source code

‍

‍

‍