Implementation of ICP Slam Algorithm on Fire Bird V for Mapping of an Indoor Environment

Abstract

Mapping and Exploration are the fundamental tasks in many mobile robotic applications such as warehouse management, search and rescue operations in disaster scenarios, service robotics, patrolling and autonomous driving. Single robots are employed in the above-said tasks to model the environment accurately and perform complex autonomous navigation tasks. Due to robustness and fault-tolerant nature, multi-robot systems are preferred over single robots for exploration tasks. Each robot in the multi-robot system explores and builds the maps of the environment individual and merges the different robots' maps to build a global map. To create a map of an unknown environment, each robot should perform SLAM. Simultaneous Localization and Mapping (SLAM) is widely used in mobile robots for self-localization and mapping the environment. The ICP (Iterative Closest Point) is one of the best approaches for SLAM. The implementation of ICP-SLAM for multi-robot systems to map the indoor environment is described here. This method is tested on the Firebird V robot equipped with RPLiDAR.