Autonomous Pipeline Tracking Using Bernoulli Filter for Unmanned Underwater Surveys

Abstract

Inspection of subsea pipelines is crucial for avoiding any hazards and minimizing the risks to infrastructure and the environment. These inspections are achieved using Autonomous Underwater Vehicles (AUVs) in favour of reduced operational costs. This work presents a vehicle agnostic approach for tracking subsea pipelines at close-range for autonomous guidance along the pipeline using an AUV. A multibeam echosounder is used as the primary tracking sensor augmented by fluxgate magnetometers that can track buried pipelines over short ranges until they are exposed again. A Bernoulli filter is proposed to efficiently track pipelines in presence of environmental clutter. Field experiments were carried out in a dock and at sea to evaluate the proposed system and the benefits of using a Bernoulli filter over a Kalman filter-based solution.