Design of Unmanned Underwater Vehicle (UUV) For Precision Targeting Using Simple PID-Controler

A model of an Unmanned Underwater Vehicle (UUV) for precision targeting using simple PID controller has been designed. The system has been assumed to have two-dimensional character, such that the mechanical control mechanism would be performed solely by rudder. A GPS/IMU system was employed in the model to provide the exact location and current trajectory direction and will be used to compared between the instantaneous correct direction and instantaneous current direction. This difference would drive PID control system to give correct angle deflection of the rudder. Some parameters of the PID controller has to be well-tuned employing several schemes including the Routh-Hurwitz stability criterion. Keywords: UUV, PID Controller, Precision Targeting, GPS, IM

A Survey of Recent Machine Learning Solutions for Ship Collision Avoidance and Mission Planning

Machine Learning (ML) techniques have gained significant traction as a means of improving the autonomy of marine vehicles over the last few years. This article surveys the recent ML approaches utilised for ship collision avoidance (COLAV) and mission planning. Following an overview of the ever-expanding ML exploitation for maritime vehicles, key topics in the mission planning of ships are outlined. Notable papers with direct and indirect applications to the COLAV subject are technically reviewed and compared. Critiques, challenges, and future directions are also identified. The outcome clearly demonstrates the thriving research in this field, even though commercial marine ships incorporating machine intelligence able to perform autonomously under all operating conditions are still a long way off.Peer reviewe

A Survey of Recent Machine Learning Solutions for Ship Collision Avoidance and Mission Planning

Machine Learning (ML) techniques have gained significant traction as a means of improving the autonomy of marine vehicles over the last few years. This article surveys the recent ML approaches utilised for ship collision avoidance (COLAV) and mission planning. Following an overview of the ever-expanding ML exploitation for maritime vehicles, key topics in the mission planning of ships are outlined. Notable papers with direct and indirect applications to the COLAV subject are technically reviewed and compared. Critiques, challenges, and future directions are also identified. The outcome clearly demonstrates the thriving research in this field, even though commercial marine ships incorporating machine intelligence able to perform autonomously under all operating conditions are still a long way off

Evaluation of the utility and performance of an autonomous surface vehicle for mobile monitoring of waterborne biochemical agents

Real-time water quality monitoring is crucial due to land utilization increases which can negatively impact aquatic ecosystems from surface water runoff. Conventional monitoring methodologies are laborious, expensive, and spatio-temporally limited. Autonomous surface vehicles (ASVs), equipped with sensors/instrumentation, serve as mobile sampling stations that reduce labor and enhance data resolution. However, ASV autopilot navigational accuracy is affected by environmental forces (wind, current, and waves) that can alter trajectories of planned paths and negatively affect spatio-temporal resolution of water quality data. This study demonstrated a commercially available solar powered ASV equipped with a multi-sensor payload ability to operate autonomously to accurately and repeatedly maintain established A-B line transects under varying environmental conditions, where lateral deviation from a planned linear route was measured and expressed as cross-track error (XTE). This work provides a framework for development of spatial/temporal resolution limitations of ASVs for real-time monitoring campaigns and future development of in-situ sampling technologies

Modelling and control of a UAV-USV collaboration scheme for fluvial operations

This thesis focuses on a Model Based Design approach to the dynamic modelling and control design of a multi-robot solution based on a collab- oration scheme between a UAV and USV. The purpose of the system is to provide a suitable platform to autonomously perform limnology related surveys. The dynamic models of both platforms are derived from a Newton- Euler formalism and implemented through block oriented modelling us- ing the Simscape Multibody toolset within Simulink. The implementation of both the simulation architecture and the control architecture are de- scribed and explained. This control architecture is based on PID feedback loops that are used for achieving control of the UAV and USV dynamics. Finally, the built simulator is used to asses the performance and relia- bility of the designed controllers and the dynamic modelling approaches selectedIngeniería en Tecnologías Industriale

UNMANNED SURFACE VEHICLE – TRITOR

This paper presents an unmanned surface vehicle Tritor that was developed, constructed, and tested within an innovative, multi-purpose, multidisciplinary, low-budget and environmentally friendly solution. The idea behind this work was trying to invent a new concept of a miniature surface vehicle that will be unmanned, remotely controlled and autonomous, with electric propulsion, and with an innovative Three Slender Cylinders Hull (3SCH) form gaining advantages in comparison to existing surface vehicles. This initial work is focused on vehicle prototype design, propulsion system development and optimization, control design, and trials, while research related to advantages of the vehicle in terms of naval architecture criteria such as drag and power, stability, seakeeping, and maneuverability will be investigated in further work. In addition, the paper intends to contribute to a new trend in developing vehicles with electrical propulsion that could use renewable sources of energy such as wind and solar energy. The potential usage of the vehicle can be civilian or military, and further work will be focused on larger models, improved based on the experience got during the development of the vehicle. Tritor vehicle was successfully designed, constructed, and tested in real environmental conditions. The preliminary results show that the vehicle has required performances and potential for improvements in the future. The main scientific contribution of this work is advanced surface vehicle development with a focus on a new hull form and the integration of electric propulsion in it

Controlling a cargo ship without human experience based on deep Q-network

Human experience is regarded as an indispensable part of artificial intelligence in the process of controlling or decision making for autonomous cargo ships. In this paper, a novel Deep Q-Network-based (DQN) approach is proposed, which performs satisfactorily in controlling a cargo ship automatically without any human experience. At the very beginning, we use the model of KRISO Very Large Crude Carrier (KVLCC2) to describe a cargo ship. To manipulate this ship has to conquer great inertia and relatively insufficient driving force. Subsequently, customary waterways, regulations, conventions are described with Artificial Potential Field and value-functions in DQN. Based on this, the artificial intelligence of planning and controlling a cargo ship can be obtained by undertaking sufficient training, which can control the ship directly, while avoiding collisions, keeping its position in the middle of the route as much as possible. In simulation experiments, it is demonstrated that such an approach performs better than manual works and other traditional methods in most conditions, which makes the proposed method a promising solution in improving the autonomy level of cargo ships

AutoTuning Environment for Static Obstacle Avoidance Methods Applied to USVs

This work is focused on reactive Static Obstacle Avoidance (SOA) methods used to increase the autonomy of Unmanned Surface Vehicles (USVs). Currently, there are multiple approaches to avoid obstacles, which can be applied to different types of USV. In order to assist in the choice of the SOA method for a particular vessel and to accelerate the pretuning process necessary for its implementation, this paper proposes a new AutoTuning Environment for Static Obstacle Avoidance (ATESOA) methods applied to USVs. In this environment, a new simplified modelling of a LIDAR (Laser Imaging Detection and Ranging) sensor is proposed based on numerical simulations. This sensor model provides a realistic environment for the tuning of SOA methods that, due to its low load computation, is used by evolutionary algorithms for the autotuning. In order to analyze the proposed ATESOA, three SOA methods were adapted and implemented to consider the measurements given by the LIDAR model. Furthermore, a mathematical model is proposed and evaluated for using as USV in the simulation enviroment. The results obtained in numerical simulations show how the new ATESOA is able to adjust the SOA methods in scenarios with different obstacle distributions

A COLLISION AVOIDANCE SYSTEM FOR AUTONOMOUS UNDERWATER VEHICLES

The work in this thesis is concerned with the development of a novel and practical collision avoidance system for autonomous underwater vehicles (AUVs). Synergistically, advanced stochastic motion planning methods, dynamics quantisation approaches, multivariable tracking controller designs, sonar data processing and workspace representation, are combined to enhance significantly the survivability of modern AUVs. The recent proliferation of autonomous AUV deployments for various missions such as seafloor surveying, scientific data gathering and mine hunting has demanded a substantial increase in vehicle autonomy. One matching requirement of such missions is to allow all the AUV to navigate safely in a dynamic and unstructured environment. Therefore, it is vital that a robust and effective collision avoidance system should be forthcoming in order to preserve the structural integrity of the vehicle whilst simultaneously increasing its autonomy. This thesis not only provides a holistic framework but also an arsenal of computational techniques in the design of a collision avoidance system for AUVs. The design of an obstacle avoidance system is first addressed. The core paradigm is the application of the Rapidly-exploring Random Tree (RRT) algorithm and the newly developed version for use as a motion planning tool. Later, this technique is merged with the Manoeuvre Automaton (MA) representation to address the inherent disadvantages of the RRT. A novel multi-node version which can also address time varying final state is suggested. Clearly, the reference trajectory generated by the aforementioned embedded planner must be tracked. Hence, the feasibility of employing the linear quadratic regulator (LQG) and the nonlinear kinematic based state-dependent Ricatti equation (SDRE) controller as trajectory trackers are explored. The obstacle detection module, which comprises of sonar processing and workspace representation submodules, is developed and tested on actual sonar data acquired in a sea-trial via a prototype forward looking sonar (AT500). The sonar processing techniques applied are fundamentally derived from the image processing perspective. Likewise, a novel occupancy grid using nonlinear function is proposed for the workspace representation of the AUV. Results are presented that demonstrate the ability of an AUV to navigate a complex environment. To the author's knowledge, it is the first time the above newly developed methodologies have been applied to an A UV collision avoidance system, and, therefore, it is considered that the work constitutes a contribution of knowledge in this area of work.J&S MARINE LT

Overview of Key Technologies for Water-based Automatic Security Marking Platform

Water-based automatic security marking platform composed of multifunctional underwater robots and unmanned surface vessel has become the development trend and focus for exploring complex and dangerous waters,and its related technologies have flourished and gradually developed from single control to multi-platform collaborative direction in complex and dangerous waters to reduce casualties. This paper composes and analyzes the key technologies of the water-based automatic security marking platform based on the cable underwater robot and the unmanned surface vessel, describes the research and application status of the key technologies of the water-based automatic security marking platform from the aspects of the unmanned surface vessel, underwater robot and underwater multisensor information fusion, and outlooks the research direction and focus of the water automatic security inspection and marking platform