Swarm Underwater Acoustic 3D Localization: Kalman vs Monte Carlo. (27th July 2015)

• Record Type: Journal Article
• Authors: Taraglio, Sergio; Fratichini, Fabio
• Is Part Of: International journal of advanced robotic systems. Volume 12:Number 7(2015)
• Publication Date: 2015-07-27
• Subjects: Distributed Control Systems -- Mobile Robots and Intelligent Autonomous Systems -- Underwater Robots -- Sensor Fusion -- Swarm Localization; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.5772/61034
• Languages: English
• ISSNs: 1729-8806

Abstract

Two three-dimensional localization algorithms for a swarm of underwater vehicles are presented. The first is grounded on an extended Kalman filter (EKF) scheme used to fuse some proprioceptive data such as the vessel's speed and some exteroceptive measurements such as the time of flight (TOF) sonar distance of the companion vessels. The second is a Monte Carlo particle filter localization processing the same sensory data suite. The results of several simulations using the two approaches are presented, with comparison. The case of a supporting surface vessel is also considered. An analysis of the robustness of the two approaches against some system parameters is given.