Fuzzy Docking Guidance Using Augmented Navigation System on an AUV

Abstract

A fundamental successful docking operation requires the autonomous underwater vehicle (AUV) to be able to guide, navigate, and control itself into the docking station in a strategic manner and even possibly execute different maneuvers at different mission phases, depending on docking scenario, requirements, and homing sensor type. A docking station, due to environmental or mission requirements, is possibly oriented at a specific direction instead of allowing omnidirectional homing, and necessitates vehicle docking in only this direction. Depending on the operating environment, either wave or current presence or both can result in a dominating disturbance to the vehicle docking operation. In this work, an inverted ultrashort baseline (USBL) system is used as the main homing sensor to complement the existing navigation suite on the DSO-developed AUV. A docking guidance system was designed and implemented using the Sugeno fuzzy inference system (FIS). A desired heading vector field and the fuzzy rules were developed to perform the fuzzy docking maneuver. An error-state Kalman filter (KF) was designed, formulated, and implemented successfully on the AUV and has proven to perform excellent relative positioning estimation in sea trials. A software architecture was designed for the docking algorithms, and implemented onto a single board computer in the AUV. A sensor fusion approach to the software programming was adopted to ensure that navigation data from all navigation sensors are properly acquired and synchronized. A docking station was designed and eventually deployed at sea for docking trials. Successful AUV docking attempts at sea trials were demonstrated, thus showing the effectiveness of the implemented docking algorithms.

Autonomous docking using direct optimal control

“…Despite this, and contrary to topics such as path following/tracking and control allocation, research on autonomous docking for surface vessels has seen little attention. While there are some methods such as Rae and Smith (1992); Teo et al (2015); Hong et al (2003) developed for Autonomous Underwater Vehicles (AUVs), which use fuzzy control schemes for different stages of the docking process. While Breivik and Loberg (2011) and Woo et al (2016) have developed methods for Unmanned Surface Vehicles (USVs) based on target tracking and artificial potential fields respectively.…”

IDVD-based trajectory generator for autonomous underwater docking operations

“…These approaches might be useful at the very last stages of docking operations when an AUV is within reach and aligned with the DS, however, arriving to this point should use a different approach (which might involve using other trajectory-shape-varying missile guidance algorithms). In [10], a fuzzy logic guidance system is employed for the docking purpose and shows a remarkable flexibility in terms of heading generation with respect to the relative range and bearing of the vehicle to the funnel-shaped DS considering the current disturbances.…”

Spiral path planning for docking of underactuated vehicles with limited FOV

“…A common docking scenario presented in the literature [1]- [3] describes that position data is obtained either by a single acoustic transponder attached to the docking station or by a computer vision system that identifies certain features of the docking station. In both scenarios, the ability to update the position of the vehicle relies solely on the constant observation of a single landmark.…”