Proceedings of the Institution of Mechanical Engineers,Part M: Journal of Engineering for the Maritime Environment

Unmanned surface vehicles are becoming increasingly vital tools in a variety of maritime applications. Unfortunately, their usability is severely constrained by the lack of a reliable obstacle detection and avoidance system. In this article, one such experimental platform is proposed, which performs obstacle detection, risk assessment and path planning (avoidance) tasks autonomously in an integrated manner. The detection system is based on a vision-LIDAR (light detection and ranging) system, whereas a heuristic path planner is utilised. A unique property of the path planner is its compliance with the marine collision regulations. It is demonstrated through hardware-in-the-loop simulations that the proposed system can be useful for both uninhabited and manned vessels.

Autonomous underwater vehicles operating near the sea surface are subject to wave disturbances in their motion, which can affect severely the data acquisition during the vehicle motion. Bathymetric maps, for example, may suffer a big loss in quality due to such kind of disturbances that can impose oscillations in the vehicle depth and attitude. This article describes a controller structure for compensating the wave disturbances in the vertical plane for a torpedo-like autonomous underwater vehicle, based on a modified version of the linear quadratic Gaussian with loop transfer recovery control combined with a wave filter. The proposed methodology uses additional to the classic linear quadratic Gaussian with loop transfer recovery design the measurement of non-controlled states, such as the pitch rate and heave velocity, in the control action. The wave disturbances were filtered away by a shaping filter fitted to the sea spectrum, and the sensor signals were integrated by an extended Kalman filter. The proposed control methodology was tested against the classical linear quadratic Gaussian with loop transfer recovery controller in a 6-degree-of-freedom non-linear autonomous underwater vehicle simulator, producing a better performance in most demanding conditions such high wave crests. The tests also revealed the impact of the hydroplane geometry on the controller performance, which should not be underestimated by the autopilot designer.

The dynamic, control-oriented model of an underwater glider with independently controllable wings is presented. The onboard vehicle’s actuators are a ballast tank and two hydrodynamic wings. A control strategy is proposed to improve the vehicle’s maneuverability. In particular, a switching control law, together with a backstepping feedback scheme, is designed to limit the energy-inefficient actions of the ballast tank and hence to enforce efficient maneuvers. The case study considered here is an underwater vehicle with hydrodynamic wings behind its main hull. This unusual structure is motivated by the recently introduced concept of the underwater wave glider, which is a vehicle capable of both surface and underwater navigation. The proposed control strategy is validated via numerical simulations, in which the simulated vehicle has to perform three-dimensional path-following maneuvers.

Although intrinsically marine craft are known to exhibit non-linear dynamic characteristics, modern marine autopilot system designs continue to be developed based on both linear and non-linear control approaches. This article evaluates two novel non-linear autopilot designs based on non-linear local control network and non-linear model predictive control approaches to establish their effectiveness in terms of control activity expenditure, power consumption and mission duration length under similar operating conditions. From practical point of view, autopilot with less energy consumption would in reality provide the battery-powered vehicle with longer mission duration. The autopilot systems are used to control the non-linear yaw dynamics of an unmanned surface vehicle named Springer. The yaw dynamics of the vehicle being modelled using a multi-layer perceptron-type neural network. Simulation results showed that the autopilot based on local control network method performed better for Springer. Furthermore, on the whole, the local control network methodology can be regarded as a plausible paradigm for marine control system design.

An innovative, satellite-guided search-and-rescue-system will be presented. This system utilises an autonomous rescue vessel to retrieve overboard personnel. The system acts instantaneously, which significantly increases the chance of survival. It was developed for use on special ships or offshore platforms, where workers are subject to adverse weather conditions and overboard personnel are often discovered too late. A substantial challenge is the automation of the autonomously acting rescue vehicle as well as its integration into the superior search-and-rescue-process. To ensure the fastest possible approach to the casualty without endangering the person, a cascaded control concept has been designed. Two-degree-of-freedom control concepts are used to separate the tracking performance from the disturbance rejection. The inner speed control structure is divided into two parts and consists of the control structure itself with an in-line allocation to the device configuration. The contribution mainly addresses the automation of the rescue vessel, the synthesis of the control system of the autonomously acting vehicle as well as the integration into the superior search-and-rescue-process. Finally, some test results of this complex system are shown.

In this work, model predictive control is used to provide transit and hover capabilities for an autonomous underwater vehicle where the description of the system dynamics used include terms measured experimentally. The resulting controller manoeuvres the vehicle in the presence of constraints on the actuators and results obtained from the deployment of the vehicle in an inland lake for the study of the zebra mussel, an invasive species, are also given.

The integral line-of-sight guidance law for path following applications of autonomous surface vessels is presented in a unified manner, merging intuitive and theoretical aspects of this valuable control technique. Straight line path following scenarios of underactuated surface vessels in the presence of unknown constant irrotational ocean currents are considered. The integral line-of-sight guidance and two feedback controllers are combined into a cascaded configuration where the integral effect in the line-of-sight guidance is introduced to counteract the disturbance. The chosen integration law is defined to reduce the risk of wind-up effects, and it is shown that the integral action in the line-of-sight guidance law performs a vectorial sum between the vessel relative velocity and the unknown current velocity to compensate for the drift. Moreover, only relative velocities are used in the feedback loop since the ocean current is assumed constant and irrotational. Redefining the vessel model with relative velocities significantly simplifies the control system compared to the approach based on absolute velocities. Closed-loop uniform local exponential stability is achieved for path following of straight line paths. Furthermore, in steady state, the presented guidance law paired with measurements of the absolute speed and the relative speed of the vessel yields to an estimation of the ocean current. Simulations are presented to support the theoretical results.

This article proposes a swarm-based path-following guidance system for an autonomous marine multi-vehicle system. In particular, a team of unmanned surface vehicles is required to converge to and navigate along a desired reference path, while at the same time aggregating and maintaining a range-based formation configuration. First, a separate description is given for a swarm methodology, initially developed for small ground mobile robots and exploited to aggregate the robot team, and a virtual target–based path-following guidance system developed for unmanned surface vehicles, exploited to drive not the single vehicles but the robot formation as a whole. Then, the integration of the two proposed methodologies is reported and proven, in order to guarantee the feasibility and stability of the overall guidance framework. Simulative results are proposed to validate the effectiveness of the proposed methodology and to evaluate the system performances.