Coverage Path Planning (CPP) is the task of determining a path that passes over all points of an area or volume of interest while avoiding obstacles. This task is integral to many robotic applications, such as vacuum cleaning robots, painter robots, autonomous underwater vehicles creating image mosaics, demining robots, lawn mowers, automated harvesters, window cleaners and inspection of complex structures, just to name a few. A considerable body of research has addressed the CPP problem. However, no updated surveys on CPP reflecting recent advances in the field have been presented in the past ten years. In this paper, we present a review of the most successful CPP methods, focusing in the achievements made in the past decade. Furthermore, we discuss reported field applications of the described CPP methods. This work aims to become a starting point for researchers who are initiating their endeavors in CPP. Likewise, this work aims to present a comprehensive review of the recent breakthroughs in the field, providing links to the most interesting and successful works.

This paper outlines the specifications and basic design approach taken on the development of the Girona 500, an autonomous underwater vehicle whose most remarkable characteristic is its capacity to reconfigure for different tasks. The capabilities of this new vehicle range from different forms of seafloor survey to inspection and intervention tasksManuscript received April 1, 2011; revised August 5, 2011; accepted October 7, 2011. Date of publication November 30, 2011; date of current version January 9, 2012. Recommended by Guest Editor W. Kirkwood. This work was supported in part by the TRIDENT EU FP7-Project under Grant ICT-248497, in part by the Marie Curie PERG-GA-2010-276778 (Surf3DSLAM), and in part by the Spanish Government under the projects DPI2008-06548-C03 and CTM2010-15216/MA

In this field note we detail the operations and discuss the results of an experiment conducted in the unstructured environment of an underwater cave complex, using an autonomous underwater vehicle (AUV). For this experiment the AUV was equipped with two acoustic sonar to simultaneously map the caves' horizontal and vertical surfaces. Although the caves' spatial complexity required AUV guidance by a diver, this field deployment successfully demonstrates a scan matching algorithm in a simultaneous localization and map- * The author can be also reached at Computer Vision and Robotics Institute, Universitat de Girona, 17003, Girona, Spain, amallios@eia.udg.edu.ping (SLAM) framework that significantly reduces and bounds the localization error for fully autonomous navigation. These methods are generalizable for AUV exploration in confined underwater environments where surfacing or pre-deployment of localization equipment are not feasible and may provide a useful step toward AUV utilization as a response tool in confined underwater disaster areas.

This paper proposes the use of path-planning algorithms for hovering autonomous underwater vehicles (AUVs) in applications where the robot needs to adapt online its trajectory for inspection or safety purposes. In particular, it proposes the platform Sparus II AUV and a set of planning algorithms to conduct these new AUV capabilities. These algorithms generate trajectories under motion constraints, which can be followed without deviations, to ensure the safety even when passing close to obstacles. View planning algorithms are also combined to decide the movements to be executed to discover the unexplored seabed or target, and to cover it with a camera or sonar. Online mapping with profiling sonars and online planning with fast sampling-based algorithms allow the execution of missions without any previous knowledge of the 3-D shape of the environment. Real 2-D results in an artificial harbor structure and simulated natural rocky canyon demonstrate the feasibility of the approach for avoiding or inspecting the underwater environment. These new AUV capabilities can be used to acquire images of the environment that can be used to inspect and map the habitat. Index Terms-Autonomous underwater vehicle (AUV), hovering AUV, online path planning and view planning (VP). I. INTRODUCTION C OMMERCIAL autonomous underwater vehicles (AUVs) are mainly conceived to surveying applications in which large areas must be covered and the vehicle follows safe paths at safe altitudes. New advances in sonar technology, image processing, mapping, and robotics will allow more complex missions, in which the AUV will be able to navigate at a closer distance from the seabed, it will react to the 3-D shape of the environment, and it will even perform some autonomous intervention tasks. In this context, the Underwater Robotics Research Centre of the University of Girona has been developing several AUV prototypes during more than 20 years to achieve these new capabilities. The Sparus II AUV [1] [see Fig. 1(a)] is one of them, and was conceived as a hovering AUV for surveying and inspection applications. The vehicle was developed in 2013 and during four years, many experiments have been carried out,

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