Sonar-based SLAM Using Occupancy Grid Mapping and Dead Reckoning

Abstract

This paper presents a solution for Simultaneous localization and mapping (SLAM) with an autonomous differential drive robot in an indoor environment. We extract data from sonars and analyze it to construct a map of the explored area using occupancy grid mapping. In addition, relative positioning approaches provide location using an inertial measurement unit (IMU) and wheel encoders. Localization and mapping are essential tasks for an autonomous robot's navigation or exploration without a prior map and the system is based on discrete step-wise or event modeling which guides its navigation. The system's result is compared for accuracy against an actual map. The results show that the approach is largely accurate although the resolution of the map produced could be improved.