Intelligent Navigation System for mapping unknown environments

Abstract

This work outlines an Intelligent Navigation System (INS) for autonomous robots. The primary focus of the proposed INS is to provide a logical, computationally efficient algorithm which serves as a basis to map and navigate unknown environments. For demonstrative and testing purposes, the INS was implemented both in simulation form using MATLABTM™ SIMULINK™ as well as practically, using an omni-directional robot (ODR) platform. The INS requires input data acquired from a stereo vision system mounted on the ODR, and functions by employing a spatial information spectrum of its surrounding using the data acquired by the vision system. This proposed information spectrum is a novel tool that conveys the already identified objects and information gaps (pathways the robot can travel through, to obtain more information about the unknown environment) within the vicinity of the robot, to the INS. The INS then decides the most efficient way to map and traverse this unknown environment based on this information spectrum. Experiments were carried out in a multitude of simulated environments. Metrics such as time taken to completely map these environments and the information gathered within a given time, were used to demonstrate the efficacy of the proposed algorithm. A further extension to this algorithm is proposed to handle dynamic and moving obstacles in unknown environments.