Autonomous Navigation with Collision Avoidance using ROS

Abstract

Simultaneous navigation and mapping is a modern mapping technique. The aim of SLAM is
to develop 2D environment of a location while tracking the robot’s position. This paper aims
to develop ROS enabled robot with SLAM features in order to avoid collisions and navigate
autonomously. A world is simulated using Gazebo and visualized using a tool called Rviz.
Autonomous navigation is achieved by mapping the environment and plotting the odometry.
Particle filtering is the algorithm on which SLAM works. This helps in using the odometry
values to find the probable path for the robot to move whilst avoiding collision.