Investigation of autonomous docking strategies for robotic operation on intervention panels

Abstract

This paper presents a localization strategy for an AUV which autonomously docks on intervention panels. A brief review of past research and working solutions of docking motivates the proposed choice of the strategy. It combines a ranging sonar localization technique featuring a modified particle filter at large distance and a visual model-based pose estimation using on-board camera at close distance to the docking panel. The particle filter solution is enhanced for effective exploration of the vehicle states without increasing the computational demand. It operates in an environment with a known map and has a real-time performance. The pose recognition algorithm derives from POSIT and is optimized for robustness. The visual docking utilizes a set of point-light markers which guarantees good accuracy at a large range of angles. Mentioned strategies are proven in a number of simulations as well as practical tests.978-1-4244-2620-1/08/$25.00 ©2008 IEEE

A Dual-Use Visible Light Communication and Orientation Estimation System for Underwater Robots

“…This technique of using a communication system for orientation calculation has been applied to radio and sonar systems with significantly different hardware and algorithms [5]. In addition, optical sources have been used as references for localizing robots for the purpose of docking [6]. In addition, optical localization techniques have been developed using a predetermined transmitting light pattern and various machine vision algorithms, include image "mosaic" approaches [7][8].…”

A combined particle filter and deterministic approach for underwater object localization using markers

“…Due to the SoftAssign algorithm used, this iterative method is capable in estimating object pose even in the presence of noise and occlusion. Hence, it has been used in the development of an autonomous docking system in [23]. However, in addition to being restricted to localizing only 3D object with four or more non-coplanar points, certain configuration of data or situations with large amount of clutter and occlusions might still cause the SoftPOSIT algorithm to fail [24].…”

Underwater navigation using visual markers in the context of intervention missions

“…In recent years, there has been an increasing interest in autonomous behaviors for intervention missions, that is, missions with autonomous underwater vehicles (AUVs) or at least semiautonomous remotely operated vehicles (ROVs), which include automated, machine-controlled manipulation tasks. [1][2][3][4][5][6][7][8][9] Surveillance and inspection missions are usually not so critical in terms of navigation performance. For these missions, the vehicle observes the environment only from a distance and the localization accordingly needs to be only reasonably accurate.…”