I-AUV Docking and Panel Intervention at Sea

The use of commercially available autonomous underwater vehicles (AUVs) has increased during the last fifteen years. While they are mainly used for routine survey missions, there is a set of applications that nowadays can be only addressed by manned submersibles or work-class remotely operated vehicles (ROVs) equipped with teleoperated arms: the intervention applications. To allow these heavy vehicles controlled by human operators to perform intervention tasks, underwater structures like observatory facilities, subsea panels or oil-well Christmas trees have been adapted, making them more robust and easier to operate. The TRITON Spanish founded project proposes the use of a light-weight intervention AUV (I-AUV) to carry out intervention applications simplifying the adaptation of these underwater structures and drastically reducing the operational cost. To prove this concept, the Girona 500 I-AUV is used to autonomously dock into an adapted subsea panel and once docked perform an intervention composed of turning a valve and plugging in/unplugging a connector. The techniques used for the autonomous docking and manipulation as well as the design of an adapted subsea panel with a funnel-based docking system are presented in this article together with the results achieved in a water tank and at sea.This work was supported by the Spanish project DPI2014-57746-C3 (MERBOTS Project) and by Generalitat Valenciana under Grant GVA-PROMETEO/2016/066. The University of Girona wants to thank the SARTI group for their collaboration with the TRITON project

I-AUV Docking and Panel Intervention at Sea

The use of commercially available autonomous underwater vehicles (AUVs) has increased during the last fifteen years. While they are mainly used for routine survey missions, there is a set of applications that nowadays can be only addressed by manned submersibles or work-class remotely operated vehicles (ROVs) equipped with teleoperated arms: the intervention applications. To allow these heavy vehicles controlled by human operators to perform intervention tasks, underwater structures like observatory facilities, subsea panels or oil-well Christmas trees have been adapted, making them more robust and easier to operate. The TRITON Spanish founded project proposes the use of a light-weight intervention AUV (I-AUV) to carry out intervention applications simplifying the adaptation of these underwater structures and drastically reducing the operational cost. To prove this concept, the Girona 500 I-AUV is used to autonomously dock into an adapted subsea panel and once docked perform an intervention composed of turning a valve and plugging in/unplugging a connector. The techniques used for the autonomous docking and manipulation as well as the design of an adapted subsea panel with a funnel-based docking system are presented in this article together with the results achieved in a water tank and at sea.This work was supported by the Spanish project DPI2014-57746-C3 (MERBOTS Project) and by Generalitat Valenciana under Grant GVA-PROMETEO/2016/066. The University of Girona wants to thank the SARTI group for their collaboration with the TRITON project

Cooperative Rendezvous and Docking for Underwater Robots Using Model Predictive Control and Dual Decomposition

This paper considers the problem of rendezvous and docking with visual constraints in the context of underwater robots with camera-based navigation. The objective is the convergence of the vehicles to a common point while maintaining visual contact. The proposed solution includes the design of a distributed model predictive controller based on dual decomposition, which allows for optimization in a decentralized fashion. The proposed distributed controller enables rendezvous and docking between vehicles while maintaining visual contact.acceptedVersion© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

Explainable Planning

As AI is increasingly being adopted into application solutions, the challenge of supporting interaction with humans is becoming more apparent. Partly this is to support integrated working styles, in which humans and intelligent systems cooperate in problem-solving, but also it is a necessary step in the process of building trust as humans migrate greater responsibility to such systems. The challenge is to find effective ways to communicate the foundations of AI-driven behaviour, when the algorithms that drive it are far from transparent to humans. In this paper we consider the opportunities that arise in AI planning, exploiting the model-based representations that form a familiar and common basis for communication with users, while acknowledging the gap between planning algorithms and human problem-solving.Comment: Presented at the IJCAI-17 workshop on Explainable AI (http://home.earthlink.net/~dwaha/research/meetings/ijcai17-xai/). Melbourne, August 201

Gnirut: The Trouble With Being Born Human In An Autonomous World

What if we delegated so much to autonomous AI and intelligent machines that They passed a law that forbids humans to carry out a number of professions? We conceive the plot of a new episode of Black Mirror to reflect on what might await us and how we can deal with such a future.Comment: 5 pages, 0 figures, Accepted at the "Re-Coding Black Mirror" workshop of the International World Wide Web Conferences (WWW

Simultaneous Trajectory Estimation and Mapping for Autonomous Underwater Proximity Operations

Due to the challenges regarding the limits of their endurance and autonomous capabilities, underwater docking for autonomous underwater vehicles (AUVs) has become a topic of interest for many academic and commercial applications. Herein, we take on the problem of state estimation during an autonomous underwater docking mission. Docking operations typically involve only two actors, a chaser and a target. We leverage the similarities to proximity operations (prox-ops) from spacecraft robotic missions to frame the diverse docking scenarios with a set of phases the chaser undergoes on the way to its target. We use factor graphs to generalize the underlying estimation problem for arbitrary underwater prox-ops. To showcase our framework, we use this factor graph approach to model an underwater homing scenario with an active target as a Simultaneous Localization and Mapping problem. Using basic AUV navigation sensors, relative Ultra-short Baseline measurements, and the assumption of constant dynamics for the target, we derive factors that constrain the chaser's state and the position and trajectory of the target. We detail our front- and back-end software implementation using open-source software and libraries, and verify its performance with both simulated and field experiments. Obtained results show an overall increase in performance against the unprocessed measurements, regardless of the presence of an adversarial target whose dynamics void the modeled assumptions. However, challenges with unmodeled noise parameters and stringent target motion assumptions shed light on limitations that must be addressed to enhance the accuracy and consistency of the proposed approach.Comment: 19 pages, 14 figures, submitted to the IEEE Journal of Oceanic Engineerin

Oceanus.

v. 34, no. 1 (1991