Trajectory Planning for Autonomous Underwater Vehicles: A Stochastic Optimization Approach

الموضوعات

علوم تطبيقية وتكنولوجية

الملخص

In this dissertation, we develop a new framework for 3D trajectory planning of Autonomous Underwater Vehicles (AUVs) in realistic ocean scenarios. The work is divided into three parts. In the first part, we provide a new approach for deterministic trajectory planning in steady current, described using Ocean General Circulation Model (OGCM) data. We apply a Non-Linear Programming (NLP) to the optimal-time trajectory planning problem. To demonstrate the effectivity of the resulting model, we consider the optimal time trajectory planning of an AUV operating in the Red Sea and the Gulf of Aden. In the second part, we generalize our 3D trajectory planning framework to time-dependent ocean currents. We also extend the framework to accommodate multi-objective criteria, focusing specifically on the Pareto front curve between time and energy. To assess the effectiveness of the extended framework, we initially test the methodology in idealized settings. The scheme is then demonstrated for time-energy trajectory planning problems in the Gulf of Aden. In the last part, we account for uncertainty in the ocean current field, is described by an ensemble of flow realizations. The proposed approach is based on a non-linear stochastic programming methodology that uses a risk-aware objective function, accounting for the full variability of the flow ensemble. We formulate stochastic problems that aim to minimize a risk measure of the travel time or energy consumption, using a flexible methodology that enables the user to explore various objectives, ranging seamlessly from risk-neutral to risk-averse. The capabilities of the approach are demonstrated using steady and transient currents. Advanced visualization tools have been further designed to simulate results.

روابط وملفات

التعريف والنوع

رقم الوثيقة

fbcda6ce-5c7c-4b2b-a2a1-4439a47e00ef

رقم العقد

0

نوع الوسائط

Crawler

نوع المحتوى

الرسائل العلمية

صيغة المصدر

رسائل دكتوراة

نوع الملف

pdf text

أسماء الملفات

2021315_1.pdf

بيانات النشر

ألقاب المؤلفين

[{"name_ar":"Omar Knio","title_ar":"اشراف","title_en":"Supervision"},{"name_ar":"Sultan Saud Albarakati","title_ar":"اعداد","title_en":"Preparation"}]

اللغة

English

المصدر والدورية

اسم المصدر

Trajectory Planning for Autonomous Underwater Vehicles: A Stochastic Optimization Approach

المحتوى والصفحات

عدد الصفحات

0

إشراف وإعداد

الإشراف

Omar Knio

الإعداد

Sultan Saud Albarakati

الاقتباسات الببليوغرافية