Path‐following algorithms and experiments for an unmanned surface vehicle

This paper focuses on the control strategy needed by marine robots to be able to follow moving paths within a cooperative framework. This control aspect is essential in order to effectively perform emergency ship towing operations. In particular, these robots coordinate their motion, with the aim of performing an autonomous tying operation, linking the messenger line of a distressed ship to a salvage tugboat. Automatic guidance algorithms are developed in order to provide cooperation and coordination of robots' motion, in such a way to perform the knotting maneuver between the two employed vehicles. In particular, the major contribution of the present work in terms of adaptive control methodology consists in extending a wellknown path following strategy for multi-vehicle cooperation to cope with moving reference paths. Extensive experimental testing validates the proposed concept, also pointing out the feasibility and effectiveness of the developed system in real-case scenarios.

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“…Following the analysis carried out in [6], the kinematic equations have to be rewritten keeping into account the path velocity:…”

Section: Circle-following Guidancementioning

confidence: 99%

Cooperative adaptive guidance and control paradigm for marine robots in an emergency ship towing scenario

Bruzzone

Bibuli

Zereik

et al. 2016

Adaptive Control & Signal

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“…Path following for nonholonomic and underactuated vehicles [Bibuli et al, 2009, Sordalen and Canudas de Wit, 1993, Soetanto et al, 2003, Micaelli and Samson, 1993, Aircardi et al, 2001] provides convergence to curves in space, though not necessarily convergence to a time-parameterized trajectory. Trajectory tracking controllers drive the full state of a system to a desired time-varying reference state.…”

Section: Trajectory Trackingmentioning

confidence: 99%

Modeling, Identification, and Control of an Unmanned Surface Vehicle

Sonnenburg

Woolsey

2013

Journal of Field Robotics

139

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This dissertation addresses the modeling, identification, and control of an automated planing vessel. To provide motion models for trajectory generation and to enable model-based control design for trajectory tracking, several experimentally identified models are compared over a wide range of speed and planing conditions for the Virginia Tech Ribcraft Unmanned Surface Vehicle. The modeling and identification objective is to determine a model which is sufficiently rich to enable effective model-based control design and trajectory optimization, sufficiently simple to allow parameter identification, and sufficiently general to describe a variety of hull forms and actuator configurations. Beginning with a 6 degree of freedom nonlinear dynamic model, several linear steering and speed models are obtained as well as a thruster model.The Ribcraft USV tracks trajectories generated with the selected maneuvering models by using a backstepping trajectory controller. A PD cascade trajectory control law is also developed and the performance of the two controllers is compared using aggressive trajectories. The backstepping control law compares favorably to the PD cascade controller. The backstepping control law is then further modified to account for nonlinear sternward dynamics and for a constant or slowly varying fluid flow. ACKNOWLEDGMENTSThis dissertation is the product of the culmination of years of research and field experimentation that required the collective abilities only found in a group of skilled researchers. There are many people that guided me through the higher level decision-making and advising process as well as the more laborious experimentation and implementation efforts. Without these people I would not have been able to finish a dissertation even approaching this quality.

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“…1, operate in open environments and handle many tasks, such as station keeping [17], path following [1], or environmental monitoring [7,8]. Those researches demonstrated that a low precision two-dimensional (2D) state estimation based on GPS and compass measurements is sufficient for such applications.…”

Section: Introductionmentioning

confidence: 99%

State Estimation for Shore Monitoring Using an Autonomous Surface Vessel

Hitz

Pomerleau

Colas

et al. 2015

Experimental Robotics

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Abstract. Although many applications of small Autonomous Surface Vessels rely on two-dimensional state estimation, inspection tasks based on long-range sensors require more accurate attitude estimates. In the context of shoreline monitoring relying on a nodding laser scanner, we evaluate three different extended Kalman filter approaches with respect to an accurate ground truth in the range of millimeters. Our experimental setup allowed us to track the impact of sensors noise, including GPS non-Gaussian error, a phenomenon often underestimated. Extensive field experiments demonstrate that the use of a complementary filter in combination with a model-based extended Kalman filter performed best and reduced velocity errors by 73% compared to GPS. Finally, following our state estimation observations, we present a long-term shore monitoring result highlighting changes in the environment over a period of 6 months.

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Path‐following algorithms and experiments for an unmanned surface vehicle

Cited by 117 publications

References 34 publications

Cooperative adaptive guidance and control paradigm for marine robots in an emergency ship towing scenario

Cooperative adaptive guidance and control paradigm for marine robots in an emergency ship towing scenario

Modeling, Identification, and Control of an Unmanned Surface Vehicle

State Estimation for Shore Monitoring Using an Autonomous Surface Vessel

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