Autopilot Design for Unmanned Surface Vehicle based on CNN and ACO

There is a growing concern to design intelligent controllers for autopiloting unmanned surface vehicles as solution for many naval and civilian requirements. Traditional autopilot’s performance declines due to the uncertainties in hydrodynamics as a result of harsh sailing conditions and sea states. This paper reports the design of a novel nonlinear model predictive controller (NMPC) based on convolutional neural network (CNN) and ant colony optimizer (ACO) which is superior to a linear proportional integral-derivative counterpart. This combination helps the control system to deal with model uncertainties with robustness. The results of simulation and experiment demonstrate the proposed method is more efficient and more capable to guide the vehicle through LOS waypoints particularly in the presence of large disturbances

Концептуальные основы адаптивных авторулевых

Проблематика. Роботу присвячено критичному аналізу літератури, що охоплює головні аспекти створення адаптивних систем керування рухом судна. Мета дослідження. Метою роботи є визначення перспективних напрямів досліджень у галузі створення адаптивних систем керування рухом судна. Методика реалізації. Проведено аналіз існуючих підходів до ідентифікації параметрів моделі судна (зокрема, ідентифікації на зиґзаґу, на циркуляції та за допомогою калманівської фільтрації), визначено переваги і недоліки цих методів, що можуть бути покладені в основу створення адаптивних автостернових. Наведено критичний аналіз підходів до керування судном за допомогою класичних та новітніх методів автоматичного керування об’єктами, зокрема параметричного настроювання класичних ПІД-регуляторів, перемикання регуляторів, застосування нелінійних регуляторів – лінійно-квадратичних (LQ), “ковзного режиму” (sliding mode), а також штучного інтелекту – нейромереж, нечіткої логіки та гібридних підходів. Окремо в огляді наведено аналіз розробок вітчизняних авторів, присвячених розробці адаптивних автостернових та адаптивному керуванню рухом судна. Результати дослідження. В результаті аналізу літературних джерел визначено перспективні напрями досліджень у галузі створення адаптивних систем керування рухом судна. Висновки. Перспективними напрямами досліджень є: 1) розробка нових підходів до ідентифікації параметрів моделі руху судна та збурень, що діють на нього; 2) застосування методів штучного інтелекту, зокрема нечіткої логіки та нейромереж, до адаптивного керування судном; 3) побудова адаптивних нелінійних систем керування рухом судна.Background. The paper is devoted to critical analysis of literature that covers the major aspects of adaptive ship motion control systems. Objective. The objective of a study is identifying the promising areas of research in the field of adaptive ship motion control. Methods. The analysis of existing approaches to ship model parameters identification (including identification during zig-zag motion, during circulation and identification using Kalman filtering) is done; advantages and disadvantages of those methods are determined. The methods mentioned can be used as a basis for creating adaptive gyropilots. A critical review of approaches to ship control by means of classical and modern methods of automatic control, including the parametric adjustment of classic PID regulators, switching of regulators, use of nonlinear regulators — linear-quadratic (LQ), sliding mode regulators, and artificial intelligence — neural networks, fuzzy logic and hybrid approaches, is done. Separately, in the survey analysis of papers of Ukrainian authors, which are devoted to the development of adaptive gyropilots and adaptive ship motion control, is presented. Results. As a result of literature survey, prospective areas of studies in the field of adaptive ship control are determined. Conclusions. Most promising research areas are: 1) development of novel approaches to the identification of the vessel model parameters and disturbances acting on it; 2) application of artificial intelligence, including fuzzy logic and neural networks, to adaptive ship control methods; 3) development of adaptive nonlinear systems for ship motion control.Проблематика. Работа посвящена критическому анализу литературы, охватывающей основные аспекты создания адаптивных систем управления движением судна. Цель исследования. Цель работы – определение перспективных направлений исследований в области создания адаптивных систем управления движением судна. Методика реализации. Проведен анализ существующих подходов к идентификации параметров модели судна (в частности, идентификации на зигзаге, на циркуляции и с помощью калмановской фильтрации), определены преимущества и недостатки этих методов, которые могут быть положены в основу создания адаптивных авторулевых. Приведен критический анализ подходов к управлению судном с помощью классических и новых методов автоматического управления объектами, в частности параметрической настройки классических ПИД-регуляторов, переключения регуляторов, применения нелинейных регуляторов – линейно-квадратичных (LQ), “скользящего режима” (sliding mode), а также искусственного интеллекта – нейросетей, нечеткой логики и гибридных подходов. Отдельно в обзоре приведен анализ разработок отечественных авторов, посвященных разработке адаптивных авторулевых и адаптивному управлению движением судна. Результаты исследования. В результате анализа литературных источников определены перспективные направления исследований в области создания адаптивных систем управления движением судна. Выводы. Перспективными направлениями исследований являются: 1) разработка новых подходов к идентификации параметров модели движения судна и действующих на него возмущений; 2) применение методов искусственного интеллекта, в частности нечеткой логики и нейронных сетей, к адаптивному управлению судном; 3) построение адаптивных нелинейных систем управления движением судна

Global path planning and waypoint following for heterogeneous unmanned surface vehicles assisting inland water monitoring

The idea of dispatching multiple unmanned surface vehicles (USVs) to undertake marine missions has ignited a burgeoning enthusiasm on a global scale. Embarking on a quest to facilitate inland water monitoring, this paper presents a systematical approach concerning global path planning and path following for heterogeneous USVs. Specifically, by capturing the heterogeneous nature, an extended multiple travelling salesman problem (EMTSP) model, which seamlessly bridges the gap between various disparate constraints and optimization objectives, is formulated for the first time. Then, a novel Greedy Partheno Genetic Algorithm (GPGA) is devised to consistently address the problem from two aspects: (1) Incorporating the greedy randomized initialization and local exploration strategy, GPGA merits strong global and local searching ability, providing high-quality solutions for EMTSP. (2) A novel mutation strategy which not only inherits all advantages of PGA but also maintains the best individual in the offspring is devised, contributing to the local escaping efficiently. Finally, to track the waypoint permutations generated by GPGA, control input is generated by the nonlinear model predictive controller (NMPC), ensuring the USV corresponds with the reference path and smoothen the motion under constrained dynamics. Simulations and comparisons in various scenarios demonstrated the effectiveness and superiority of the proposed scheme

Automatic Control and Routing of Marine Vessels

Due to the intensive development of the global economy, many problems are constantly emerging connected to the safety of ships’ motion in the context of increasing marine traffic. These problems seem to be especially significant for the further development of marine transportation services, with the need to considerably increase their efficiency and reliability. One of the most commonly used approaches to ensuring safety and efficiency is the wide implementation of various automated systems for guidance and control, including such popular systems as marine autopilots, dynamic positioning systems, speed control systems, automatic routing installations, etc. This Special Issue focuses on various problems related to the analysis, design, modelling, and operation of the aforementioned systems. It covers such actual problems as tracking control, path following control, ship weather routing, course keeping control, control of autonomous underwater vehicles, ship collision avoidance. These problems are investigated using methods such as neural networks, sliding mode control, genetic algorithms, L2-gain approach, optimal damping concept, fuzzy logic and others. This Special Issue is intended to present and discuss significant contemporary problems in the areas of automatic control and the routing of marine vessels

Collision avoidance control for Unmanned Autonomous Vehicles (UAV): Recent advancements and future prospects

873-883The recent advances in collision avoidance technologies for unmanned vehicles such as UAVs, AUVs, AGVs, and USVs have greatly advanced the industry. Their lower cost and acceptability of high-risk missions have enabled the development of collision avoidance controllers for autonomous vehicles. These low-maintenance gadgets are also portable, need low maintenance, and enable continuous monitoring to occur near real-time. This may be said; however it would be incorrect, because collision avoidance controllers have been related with compromises that affect data dependability. Research on collision avoidance controls is quickly developing; therefore it is distributed throughout multiple papers, projects, and grey literature. This report critically reviews the recent relevant research on creating collision avoidance systems for autonomous vehicles. Typically, the assessment measures are dependent on the algorithm's use case and the platform's capabilities. The full evaluation of the benefits and drawbacks of the most prevalent approaches in the present state of the art is provided based on 7 metrics which are complexity, communication dependence, pre-mission planning, robustness, 3D compatibility, real-time performance and escape trajectories

Collision avoidance control for Unmanned Autonomous Vehicles (UAV): Recent advancements and future prospects

The recent advances in collision avoidance technologies for unmanned vehicles such as UAVs, AUVs, AGVs, and USVs have greatly advanced the industry. Their lower cost and acceptability of high-risk missions have enabled the development of collision avoidance controllers for autonomous vehicles. These low-maintenance gadgets are also portable, need low maintenance, and enable continuous monitoring to occur near real-time. This may be said; however it would be incorrect, because collision avoidance controllers have been related with compromises that affect data dependability. Research on collision avoidance controls is quickly developing; therefore it is distributed throughout multiple papers, projects, and grey literature. This report critically reviews the recent relevant research on creating collision avoidance systems for autonomous vehicles. Typically, the assessment measures are dependent on the algorithm's use case and the platform's capabilities. The full evaluation of the benefits and drawbacks of the most prevalent approaches in the present state of the art is provided based on 7 metrics which are complexity, communication dependence, pre-mission planning, robustness, 3D compatibility, real-time performance and escape trajectories

Collision Avoidance for Autonomous Surface Vessels using Novel Artificial Potential Fields

As the demand for transportation through waterways continues to rise, the number of vessels plying the waters has correspondingly increased. This has resulted in a greater number of accidents and collisions between ships, some of which lead to significant loss of life and financial losses. Research has shown that human error is a major factor responsible for such incidents. The maritime industry is constantly exploring newer approaches to autonomy to mitigate this issue. This study presents the use of novel Artificial Potential Fields (APFs) to perform obstacle and collision avoidance in marine environments. This study highlights the advantage of harmonic functions over traditional functions in modeling potential fields. With a modification, the method is extended to effectively avoid dynamic obstacles while adhering to COLREGs. Improved performance is observed as compared to the traditional potential fields and also against the popular velocity obstacle approach. A comprehensive statistical analysis is also performed through Monte Carlo simulations in different congested environments that emulate real traffic conditions to demonstrate robustness of the approach.Comment: 28 pages, 30 figure

Autonomous Drone Landings on an Unmanned Marine Vehicle using Deep Reinforcement Learning

This thesis describes with the integration of an Unmanned Surface Vehicle (USV) and an Unmanned Aerial Vehicle (UAV, also commonly known as drone) in a single Multi-Agent System (MAS). In marine robotics, the advantage offered by a MAS consists of exploiting the key features of a single robot to compensate for the shortcomings in the other. In this way, a USV can serve as the landing platform to alleviate the need for a UAV to be airborne for long periods time, whilst the latter can increase the overall environmental awareness thanks to the possibility to cover large portions of the prevailing environment with a camera (or more than one) mounted on it. There are numerous potential applications in which this system can be used, such as deployment in search and rescue missions, water and coastal monitoring, and reconnaissance and force protection, to name but a few. The theory developed is of a general nature. The landing manoeuvre has been accomplished mainly identifying, through artificial vision techniques, a fiducial marker placed on a flat surface serving as a landing platform. The raison d'etre for the thesis was to propose a new solution for autonomous landing that relies solely on onboard sensors and with minimum or no communications between the vehicles. To this end, initial work solved the problem while using only data from the cameras mounted on the in-flight drone. In the situation in which the tracking of the marker is interrupted, the current position of the USV is estimated and integrated into the control commands. The limitations of classic control theory used in this approached suggested the need for a new solution that empowered the flexibility of intelligent methods, such as fuzzy logic or artificial neural networks. The recent achievements obtained by deep reinforcement learning (DRL) techniques in end-to-end control in playing the Atari video-games suite represented a fascinating while challenging new way to see and address the landing problem. Therefore, novel architectures were designed for approximating the action-value function of a Q-learning algorithm and used to map raw input observation to high-level navigation actions. In this way, the UAV learnt how to land from high latitude without any human supervision, using only low-resolution grey-scale images and with a level of accuracy and robustness. Both the approaches have been implemented on a simulated test-bed based on Gazebo simulator and the model of the Parrot AR-Drone. The solution based on DRL was further verified experimentally using the Parrot Bebop 2 in a series of trials. The outcomes demonstrate that both these innovative methods are both feasible and practicable, not only in an outdoor marine scenario but also in indoor ones as well

A survey of formation control and motion planning of multiple unmanned vehicles

The increasing deployment of multiple unmanned vehicles systems has generated large research interest in recent decades. This paper therefore provides a detailed survey to review a range of techniques related to the operation of multi-vehicle systems in different environmental domains, including land based, aerospace and marine with the specific focuses placed on formation control and cooperative motion planning. Differing from other related papers, this paper pays a special attention to the collision avoidance problem and specifically discusses and reviews those methods that adopt flexible formation shape to achieve collision avoidance for multi-vehicle systems. In the conclusions, some open research areas with suggested technologies have been proposed to facilitate the future research development