Neural anti-collision system for Autonomous Surface Vehicle

作者：Praczyk Tomasz^*

来源：Neurocomputing, 2015, 149: 559-572.

DOI：10.1016/j.neucom.2014.08.018

• Autonomous Surface Vehicle
• Collision avoidance
• Evolutionary neural networks

Autonomous Surface Vehicles (ASV) are robots destined for the operation at water basins like lakes, canals, harbors and even open sea. They are used for different purposes, e.g. for patrol tasks, as scouts, or as a support for Navy ships. One of the main tasks of ASV is to move along a fixed path to a destination point. To this end, an anti-collision system (ACS) has to be used with the ability to lead ASV along a path and to simultaneously avoid all additional objects present at the basin, e.g. ships, sailing boats, fishing cutters, icebergs. To perform this task, the ACS implemented as an evolutionary neural network can be used. The paper describes architecture of the neural ACS, presents two neuro-evolutionary methods used to build the system, and reports the whole process of constructing it.

• 出版日期2015-2-3
• 单位中国人民解放军海军大连舰艇学院