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This paper is concerned with the distributed consensus control for a group of autonomous marine vehicles with nonlinearity and external disturbances via sampled-data communications. First, the kinematical equation of autonomous marine vehicle is established. Second, stability criteria is derived to ensure the stability of autonomous marine vehicles by combining Lyapunov function method and free-weighting matrix approach. Third, a distributed sampled-data control strategy is proposed to achieve the consensus of autonomous marine vehicles by designing suitable control parameters. Numerical simulations are provided to verify the effectiveness of the proposed consensus control approach. [ABSTRACT FROM AUTHOR]

This paper presents a review on the development and application of model predictive control (MPC) for autonomous intelligent mechatronic systems (AIMS). Starting from the conceptual analysis of "mechatronics", we analyze the characteristics and control system design requirements of AIMS. In order to fulfill the design requirements, we propose to develop a unified MPC framework for AIMS. The main MPC schemes, covering MPC basics, robust MPC, distributed MPC, Lyapunov-based MPC, event-based MPC, network-based MPC, switched MPC, fast MPC, are reviewed with an attempt to document some of the key achievements in the past decades. Furthermore, we provide the review and analysis of MPC applications to three types of mechatronic systems, including unmanned aerial vehicles (UAVs), autonomous marine vehicles (AMVs), and autonomous ground robots (AGRs). Some promising research directions and concluding remarks are presented. [ABSTRACT FROM AUTHOR]

Collisions and groundings account for a great deal of fiscal losses and human risks in the statistics of marine accidents related to ocean going vessels. With highly automated vessels offering a high degree of situational awareness, algorithms can anticipate developments and suggest timely actions to avoid or deconflict critical events, in accordance to safe navigational practices and in compliance with the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs). To avoid such accidents related to navigation, this article proposes a Short Horizon Planner (SHP) for decision support or automated route deviations, as a means to mitigate prevailing risks. The planner adopts a sampling-based planning framework that uses the concepts of cross-track error and speed loss during a steady turn, together with sampling spaces directly extracted from the electronic navigational chart to compute optimal and COLREGs compliant paths with the least deviation from the ship's nominal route. COLREGs compliance (rules 8, 13–17) is achieved through an elliptical-like representations of the given COLREGs, which rejects samples based on modified ship domains. High fidelity simulations show properties of the method and the information made available to human- or automated execution of route alterations. • A Short Horizon Planner for collision and grounding avoidance of marine crafts. • Performance indexes based on cross-track error, path elongation and speed loss. • Compliance with COLREGs rules 8, 13–17 using custom elliptical comfort zones. • Grounding avoidance using a specialised sampling scheme that triangulates the chart. • The grounding and collision avoidance is demonstrated on multiple vessel scenarios. [ABSTRACT FROM AUTHOR]

This paper presents an optimal and efficient path planner based on a shell space decomposition (SSD) scheme for autonomous underwater vehicles (AUVs) operating in cluttered and uncertain environments. In 3D space the shells define the volume between adjacent spheres, whereas in a 2D plane the shells become annuli which define the area between adjacent circles. In this scheme, the search space is decomposed into shells radiating out from start to destination with a control point placed within each region. The trajectory is then generated from the control points using Splines. This arrangement gives freedom to the placement of the control points, while still restricting the search space to reduce computation time. The SSD scheme has been integrated with a QPSO based path planner and tested to find an optimal trajectory for an AUV navigating through a variable ocean environment in the presence of obstacles. Simulation results show that the proposed SSD approach is able to obtain a more optimized trajectory than the circle/sphere constrained methods and achieve faster convergence speed than the full space searching method. Monte Carlo trials were run to assess the robustness of the SSD method, the results demonstrate the inherent superiority of the proposed SSD method. [ABSTRACT FROM AUTHOR]

Abstract: Autonomous Marine Vehicles (AMVs) are not only being required to carry out more complex tasks but also longer missions. This mainly requires effective resilient operation and efficient resource management to succeed in persistent presence at sea or ocean with minimal human interaction while maintaining seakeeping performance. Even though some of the current AMVs have a large degree of self-governance, most of them fail to support self-management (e.g. auto-maintenance during pre/in/post-mission phases). Autonomic Computing (AC) basically provides the following self-managing capabilities: self-healing, self-protecting, self-optimizing, and self-configuring. In addition, it provides systems with self-aware, self-adjusted, and self-situated abilities. AC comes from a biological metaphor based on the self-regulating capabilities of the autonomic nervous system in the human body. This paper introduces the AC concept to control architectures of AMVs to endow them with resilience and environmental efficiency. The above capabilities are to help persistent autonomy and automation endure over complex and long AMV operations. This paper presents the architectural aspects, and details of design and realization of this promising AC-based approach. It also discusses four key aspects from existing methodologies and technologies that are potential approaches to support the autonomic control architecture proposed for AMVs. Finally, future research directions are presented. [Copyright &y& Elsevier]

This research investigates the planar path planning method, particularly where straight survey line in ocean exploration is required. The smooth transition path between multiple straight survey segments in origin-departing and corner-cutting transition modes is studied. First, different transition modes of autonomous marine vehicles (AMVs) in practical ocean survey navigation are realized and distinguished. Based on the definition of different transition modes, the waypoints can be pre-assigned, generated online, or compatible with online and offline assignments. Second, to avoid wiggles of vehicles, zigzags of the tracking trajectory, and to satisfy the requirements on second-order parametric and geometric continuities, the Fermat's Spiral (FS) having advantages of low computational load and engineering practicability is selected to design the transition path between multiple straight segments. The scaling of FS segments is optimized by considering the maneuverability of AMVs. Besides, the FS is parameterized in both transition modes to simplify the subsequent guidance and control scenarios. Thirdly, the closed-form analysis on geometric and parametric continuities of spliced transition path are derived. Finally, based on the parameterized smooth path and a slender underactuated AUV, numerical simulation demonstrates the effectiveness of the FS-based path planning method under integrated origin-departing and corner-cutting transition modes. • The concept of transition modes is presented by segregating different given WP sets. • Mirrored FS segments are designed as the transition path in different modes. • Closed-form geometric and parametric continuities for spliced path are analyzed. • Proposed method has closed confinement condition & requires less computing resources. [ABSTRACT FROM AUTHOR]