Navigation Of Autonomous Marine Robots

Thomas Glotzbach spotlights that navigation within marine robotics can benefit from cooperative teams in a way that justifies the increased effort to operate several vehicles at once. He features discussions of different scenarios, modeling of systems, and estimation algorithms for comparable situations. The chapter on the used methodologies may allow a reader with only basic knowledge in control theory to obtain deeper insight in advanced concepts such as observability and state estimation, even without any background in marine robotics.

Robotic marine vessels can be used for a wide range of purposes, including defence, marine science, offshore energy and hydrographic surveys, and environmental surveys and protection. Such vessels need to meet a variety of criteria: they must be able to operate in salt water, and to communicate and be controlled over large distances, even when submerged or in inclement weather. Further challenges include 3D navigation of individual vehicles, groups or squadrons. This book covers the current state of research in navigation, modelling and control of marine autonomous vehicles, and deals with various related topics, including collision avoidance, communication, and a range of applications. It provides valuable insights for an audience of researchers, academics and postgraduate students interested in autonomous marine vessels, robotics, and electrical and automobile engineering.

Autonomy for Marine Robots provides a timely and insightful overview of intelligent autonomy in marine robots. A brief history of this emerging field is provided, along with a discussion of the challenges unique to the underwater environment and their impact on the level of intelligent autonomy required. Topics covered at length examine advanced frameworks, path-planning, fault tolerance, machine learning, and cooperation as relevant to marine robots that need intelligent autonomy.

This book reports on findings at the intersection between two related fields, namely coastal hydrography and marine robotics. On one side, it shows how the exploration of the ocean can be performed by autonomous underwater vehicles; on the other side, it shows how some methods from hydrography can be implemented in the localization and navigation of such vehicles, e.g. for target identification or path finding. Partially based on contributions presented at the conference Quantitative Monitoring of Underwater Environment, MOQESM, held on October 11-12, 2016, Brest, France, this book includes carefully revised and extended chapters presented at the conference, together with original papers not related to the event. All in all, it provides readers with a snapshot of current methods for sonar track registration, multi-vehicles control, collective exploration of underwater environments, optimization of propulsion systems, among others. More than that, the book is aimed as source of inspiration and tool to promote further discussions and collaboration between hydrographers, robotic specialists and other related communities.

This book covers the current state of research in navigation, modelling and control of marine autonomous vehicles, and deals with various related topics, including collision avoidance, communication, and a range of applications.

This book presents an Intelligent Control Architecture (ICA) to enable multiple collaborating marine vehicles to autonomously carry out underwater intervention missions. The presented ICA is generic in nature but aimed at a case study where a marine surface craft and an underwater vehicle are required to work cooperatively. It is shown that they are capable of cooperating autonomously towards the execution of complex activities since they have different but complementary capabilities. The ICA implementation is verified in simulation, and validated in trials by means of a team of autonomous marine robots. This book also presents architectural details and evaluation scenarios of the ICA, results of simulations and trials from different maritime operations, and future research directions.

Marine robots are playing important roles in environmental sensing and ocean observation applications. This tutorial introduces the overall systems architecture and patterns for data streams that enable autonomy for marine robots in environmental sensing applications. The article proposes the concept of cyber-maritime cycle and surveys its use as a recent development in marine robotics. Supported by communication networks, autonomy can be achieved using at least three feedback loops in a cyber-maritime cycle, each running at different time scales or temporal frequencies. When information is circulating around the cycle, it is transformed between two representations: the Lagrangian view and the Eulerian view. Important functional blocks, such as mission planning, path planning, data assimilation, and data-driven modeling are discussed as providing conversions between the two views of data. The tutorial starts with an overview of enabling technologies in sensing, navigation, and communication for marine robotics. The design of experiment method is then reviewed to plan optimal sensing locations for the robots. The tutorial discusses a class of path planning methods that produces desired trajectories of marine robots while combating ocean current. The lack of an accurate Eulerian map for ocean current will lead to tracking error when robots attempt to follow the planned paths to collect Lagrangian data. The performance of robot navigation can be evaluated through the controlled Lagrangian particle tracking method, which computes trends and bounds for the growth of the tracking error. To improve the accuracy of the Eulerian map of ocean current, a data-driven modeling approach is adopted. Data assimilation methods are leveraged to convert Lagrangian data into Eulerian map. In addition, the spatial and temporal resolution of Eulerian data maps can be further improved by the motion tomography method. This tutorial gives a comprehensive view of data streams and major functional blocks underlying autonomy of marine robots.

The presence of mobile robots in diverse scenarios is considerably increasing to perform a variety of tasks. Among them, many developments have occurred in the fields of ground, underwater, and flying robotics. Independent of the environment where they move, navigation is a fundamental ability of mobile robots so that they can autonomously complete high-level tasks. This problem can be efficiently addressed through the following actions: First, it is necessary to perceive the environment in which the robot has to move, and extract some relevant information (mapping problem). Second, the robot must be able to estimate its position and orientation within this environment (localization problem). With this information, a trajectory toward the target points must be planned (path planning), and the vehicle must be reactively guided along this trajectory considering either possible changes or interactions with the environment or with the user (control). Given this information, this book introduces current frameworks in these fields (mapping, localization, path planning, and control) and, in general, approaches to any problem related to the navigation of mobile robots, such as odometry, exploration, obstacle avoidance, and simulation.