Bio Inspired Approaches for Indoor Path Navigation and Spatial Map Formation by Analysing Depth Data

Abstract

Indoor Navigation presents a significant domain for carrying out with research issues. Literature review depicts inspite of having various existing graph theoretic optimization approaches for safe path exploration, the mobile robot faces difficulties in achieving robust and efficient computation. The cause of difficulties include limitation in sensor availability, limitation in reachability, having dynamic on path obstacles, and space-time complexity. The paper presents a working model for mobile robot navigation by detecting objects analysing depth data in the concerned environment followed by optimized path exploration using bio inspired path planning techniques. This is accompanied by spatial map formation incorporating with Robot Operating System (ROS) environment for getting an idea of visual inference of the taken indoor environment. Analysis of working principle and respective methodology of the algorithms have been done and experimental results are noted. Comparative ease in computation and optimization are obtained and presented neatly in subsequent sections. The analysis would prove to be remarkable citation for future research in the field of Optimized Collision-free Indoor Navigation (OCIN).