Radar-based Maritime Collision Avoidance using Dynamic Window

Abstract

Collision avoidance systems are a key ingredient in developing autonomous surface vehicles (ASVs). Such systems require real-time information about the environment, which can be obtained from transponder-based systems or exteroceptive sensors located on the ASV. In this paper, we present a closed-loop collision avoidance (COLAV) system using a maritime radar for detecting target ships, implemented on a 26 foot high-speed ASV. The system was validated in full-scale experiments in Trondheimsfjorden, Norway, in May 2017. The probabilistic data association filter (PDAF) is used for tracking target vessels. The output from the PDAF is processed through a least-squares retrodiction procedure in order to provide the COLAV system with sufficiently accurate course estimates. A tracking interface provides estimates of target states to the COLAV system, which is based on the dynamic window (DW) algorithm. DW is a reactive COLAV algorithm originally designed for ground vehicles, and we therefore make a number of modifications to adapt it for use with high-speed ASVs. The closed-loop experiments demonstrated successful COLAV with this system, but also disclosed several challenges arising from both the DW algorithm and the tracking system, motivating for further work.