Unmanned surface vehicles: An overview of developments and challenges

Liu, Zhixiang; Chen, Yuan

doi:10.1016/j.arcontrol.2016.04.018

Cited by 854 publications

(425 citation statements)

References 159 publications

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“…Nevertheless, there is mention More recent compilation works, specifically directed at mobile robots, continue to cite model-based methods of fault detection as being the mostly used in robotics. Nevertheless, there is mention to the lack of effort of incorporating fault detection and diagnosis, or even to progress in the field of fault tolerance concerning Unmanned Surface Vehicles (USVs) actuators or communication systems [17]. Even in the case of UGVs, both military and rescue, an analysis showed a problem with mobile robots reliability [18].…”

Section: Overviewmentioning

confidence: 99%

A Safety Monitoring Model for a Faulty Mobile Robot

2018

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Abstract:The continued development of mobile robots (MR) must be accompanied by an increase in robotics' safety measures. Not only must MR be capable of detecting and diagnosing faults, they should also be capable of understanding when the dangers of a mission, to themselves and the surrounding environment, warrant the abandonment of their endeavors. Analysis of fault detection and diagnosis techniques helps shed light on the challenges of the robotic field, while also showing a lack of research in autonomous decision-making tools. This paper proposes a new skill-based architecture for mobile robots, together with a novel risk assessment and decision-making model to overcome the difficulties currently felt in autonomous robot design.

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Section: Overviewmentioning

confidence: 99%

A Safety Monitoring Model for a Faulty Mobile Robot

2018

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“…When building the reference frame, an origin of USV body coordinates coincides with the center of gravity, and both the center of gravity and buoyancy are perpendicular to the -axis. In physical design, USV is set to be port-starboard symmetrical; hence surge subsystem and sway-yaw subsystem are essentially decoupled [2].…”

Section: The Model Of Usvmentioning

confidence: 99%

“…According to the related literature, various designed controller approaches have been proposed like sliding mode control, adaptive control, backstepping control, cascaded control theory, fuzzy logic control, and so on. As discussed by Liu et al [2] comprehensive reviews present recent progress of the control approaches from the points of applications, methodologies, and challenges. As to the adaptive control, an active mechanism for unmanned vehicles, Klinger et al [3] implemented an adaptive algorithm with the modified backstepping surge controller which has been field tested.…”

Section: Introductionmentioning

confidence: 99%

Speed and Heading Control of an Unmanned Surface Vehicle Based on State Error PCH Principle

Hua

et al. 2018

Mathematical Problems in Engineering

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This paper proposes a novel nonlinear control scheme based on energy-shaping (ES) principle and state error port-controlled Hamiltonian (PCH) systems for unmanned surface vehicles (USV) system. The PCH model of three degrees of freedom for USV kinetics system is established. By the ES principle, interconnection assignment and damping injection method is applied to the speed and heading control of the closed-loop USV system to realize an overall stability of control mechanism. Simulation results show that the validity and stability of control algorithm can be satisfied with the performance in speed and heading tracking of which the high simplification and portability make it applicable to the various region.

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“…In line with the growing interest in the ocean for civilian and military applications, there has been an increasing demand for the autonomy of unmanned surface vehicles (USVs) with advanced automatic navigation systems (ANSs) [1]. USVs are intelligent unmanned platforms which perform tasks independently in a variety of cluttered sea environments and have highly nonlinear dynamic characteristics [2].…”

Section: Introductionmentioning

confidence: 99%

“…After planning the path, according to the guidance, navigation, and control (GNC) system structure [1] the next step is to control the USV following the path. Some works have discussed this problem after generating the path.…”

Section: Introductionmentioning

confidence: 99%

An Automatic Navigation System for Unmanned Surface Vehicles in Realistic Sea Environments

et al. 2018

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Abstract:In recent years, unmanned surface vehicles (USVs) have received notable attention because of their many advantages in civilian and military applications. To improve the autonomy of USVs, this paper describes a complete automatic navigation system (ANS) with a path planning subsystem (PPS) and collision avoidance subsystem (CAS). The PPS based on the dynamic domain tunable fast marching square (DTFMS) method is able to build an environment model from a real electronic chart, where both static and dynamic obstacles are well represented. By adjusting the Saturation, the generated path can be changed according to the requirements for security and path length. Then it is used as a guidance trajectory for the CAS through a dynamic target point. In the CAS, according to finite control set model predictive control (FCS-MPC) theory, a collision avoidance control algorithm is developed to track trajectory and avoid collision based on a three-degree of freedom (DOF) planar motion model of USV. Its target point and security evaluation come from the planned path and environmental model of the PPS. Moreover, the prediction trajectory of the CAS can guide changes in the dynamic domain model of the vessel itself. Finally, the system has been tested and validated using the situations of three types of encounters in a realistic sea environment.

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Unmanned surface vehicles: An overview of developments and challenges

Cited by 854 publications

References 159 publications

A Safety Monitoring Model for a Faulty Mobile Robot

A Safety Monitoring Model for a Faulty Mobile Robot

Speed and Heading Control of an Unmanned Surface Vehicle Based on State Error PCH Principle

An Automatic Navigation System for Unmanned Surface Vehicles in Realistic Sea Environments

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