Modelling sand ripples in mine countermeasure simulations by means of stochastic optimal control

TL;DR

This paper introduces a stochastic optimal control framework to model and simulate the impact of ocean sand ripples on autonomous mine countermeasure vehicles, improving trajectory planning for mine detection.

Contribution

It presents a novel approach to incorporate sand ripple effects into autonomous vehicle trajectory optimization using stochastic control.

Findings

Enhanced modeling of sand ripple effects on mine detection

Improved trajectory planning accuracy for autonomous vehicles

Potential for better mine detection success rates

Abstract

Modelling and simulating mine countermeasures (MCM) search missions performed by autonomous vehicles equipped with a sensor capable of detecting mines at sea is a challenging endeavour. In this work, we present a novel way to model and account for sand ripples present on the bottom of the ocean while calculating trajectories for the autonomous vehicles by means of a stochastic optimal control framework. It is known from the scientific literature that these ripples impact the sea mine detection capabilities of the autonomous vehicles.