A Nindoor lidar based autonomous mobile robot using slam and rrt algorithms

Abstract

In the past few years, we have seen a rise in autonomous robots that are able to navigate and operate in a variety of diff erent environments. Autonomous navigation robots are now capable of moving around in a given space without human intervention. They can navigate independently, avoid obstacles and fi nd their way back to a starting point. Research in the development of autonomous navigation robots is intended to enhance their autonomy in executing diff erent tasks of varying complexity levels. One of these tasks is localization, mapping, and path planning. Robot localization is the process of defi ning the location of the mobile robot as it navigates through its environment. Mapping addresses the problem of collecting spatial models of the environment by the robot as it navigates. Path planning is the process of planning an obstacle-free trajectory for the mobile robot to navigate from a starting position toward a given goal destination. This project introduces a simulation of a mobile robot navigating in a closed indoor environment. The robot uses a lidar sensor to collect data about its environment in order to build a model map of it that will be used later on for path planning purposes. Both the SLAM (Simultaneous localization and mapping) and RRT* algorithms are used for map building and trajectory planning respectively.