Simulation of a Mobile Robot with an LRF in a 2D Environment and Map Building

Abstract

This article deals with the modelling and simulation of a mobile robot with a laser range finder in a 2D environment and map building. The simulator is built in the Matlab Simulink environment, thereby taking advantage of the powerful Matlab toolboxes for developing mapping, localization, SLAM, and navigation algorithms. A map-building algorithm is developed and tested in a simulation. The line segments, extracted from the LRF’s output in each scan, are made up of polylines, which are merged with the existing global map to form a new global map. The global map of the environment is represented by unions of line segments, where each union represents an object in the environment. Map building, localization and navigation are important issues in mobile robotics. To develop and test algorithms for executing tasks of this kind, it is useful to have a simulator of a mobile robot equipped with sensors in a static environment. Since a Laser Range Finder (LRF) is often used as the basic interaction between the robot and the environment, the represented mobile robot model also includes a model of the LRF. The problem of robotic mapping and localization has been widely studied. A robot has to know its own pose (localization problem) in order to build a map, and it also needs to know the environment map (mapping problem) to localize itself to its current pose. The problems of mapping and localization can be handled separately if the robot’s pose is given to the robot by a human or from using GPS and INU sensors (outdoor environments) when map building. The map of the environment can then be used to solve the localization problem.