Developing an Energy Effective Autonomous USV for Undertaking Missions at the Highlands of Peru

Abstract

This paper describes a novel multi-task allocation method for the autonomous navigation to improve the efficiency for executing mission considering an Unmanned Surface Vehicle (USV) developed by the Pontificia Universidad Catolica del Peru (PUCP). The new method is developed based upon the self-organizing map (SOM) algorithm, with the consideration of the priorities of the sample stations that USV need to visit, as well as the lattice distances from the sample stations to the start point. Using this new method, an optimized order of visiting sequence can be calculated according to the battery energy limit of the USV. The new multi-task allocation method has been verified in simulation environments with results proving the effectiveness and capabilities of the system.