Development and Performance Analysis of Orthogonal Sonar Array for Autonomous Mobile Robot SLAM Implementation

Simultaneous Localization and Mapping (SLAM) research focuses on different techniques to develop efficient systems. Acoustic SLAM(aSLAM) is an alternative technique that is unrestricted from visual SLAM (vSLAM) limitations and is a cheaper than LiDAR SLAM. Nevertheless, current aSLAM implementations do usually require several units of ultrasonic range sensors which invalidate the advantages of aSLAM vs vSLAM. This study presents a novel aSLAM system where the number of ultrasonic range sensors is halved and combined with the possibility of varying the orientation angle between the sensors, providing a significant reduction of cost while preserving the performance. The paper presents an Orthogonal Sonar Array (OSA) setup of three sensors, which is a variation of the traditional aSLAM implementations (i.e. 6 sensors). This setup has been tested by generating a map representation of three experimental scenarios and comparing the results against a CAD model of the environment. The setup was able to successfully reconstruct the three environments with boundary accuracies of 72.91%, 77%, and 80.70% respectively. The least generated map has then been utilized as a reference to perform a path planning task and to validate the usability of the map generated from the OSA setup.