# A Data-Driven Intermittent Online Coverage Path Planning Method for AUV-Based Bathymetric Mapping  
[PERSON]  
1 College of Electronics and Information Engineering, Hangzhou Dianzi University, Hangzhou 310018, China; [EMAIL_ADDRESS]  
[PERSON]  
2 Graduate School of Oceanography, University of Rhode Island, Narragansett, RI 02882, USA  
Chart of the Oceans (GEBCO) and the Nippon Foundation [1]. Autonomous underwater vehicles (AUVs) are proved to be effective to perform mapping tasks [2]. Compared to normal ships, AUVs offer a lower operational cost and smaller carbon footprint with reduced ship usage, and they can provide higher resolution data when surveying the seabed at a closer distance due to the fact that the transversal mapping resolution decreases with the standoff distance [3]. In recent years, many researchers have applied AUVs [2; 4] to perform bathymetric mapping where multibeam sonars are mainly used. Other sonars, including single-beam sonars, side-scan sonars, and interferometric sonars, are also used. However, single beam sonars yield sparse data points, and side-scan sonars provide high resolution images instead of 3D point clouds. Interferometric sonars are special side-scan sonars which can produce bathymetry image through differential phase technique. However, they require sophisticated signal processing algorithms to get a satisfied result [5]. An important issue to be addressed in seafloor mapping with AUVs is the path planning. A good survey path provides efficient and complete coverage on the workspace, while a poorly planned path yields a tremendous amount of redundant samples or leaves possible voids in the workspace. In the literatures [2; 4; 6; 7; 8], lawnmower pattern paths (also known as boustrophedon paths) were popularly used, which is presented by simple back-and-forth transects spaced at a constant inter-distance. Lawn moving and underwater bathymetric survey both require complete coverage of a specific area, however, the lawnmower blade has a consistent cutting coverage, while the width of the multibeam sonar swath varies due to the elevation changes of the seabed. As a result, a constant inter-distance as in lawnmower paths will not be effective in bathymetric mapping. For example, a narrow inter-distance will increase the overall mission time and produce significant overlaps and redundant samples. In contrast, a wide inter-distance will result in possible voids between transects. Moreover, the multibeam footprints increase with the standoff distance. For a typical multibeam sonar, the distance between the beams and the bottom are different. This causes non-uniform confidence along the swath [9]. The term confidence here refers to the possibility of obtaining valid data and the accuracy of the measurement. The greater the footprint size, the weaker the echos from the seafloor, the fewer number of soundings that will be received [10], and the lower the confidence. Thus, the footprints of multibeam need to be considered to get high quality bathymetric maps. In this paper, we look into the characteristics of multibeam sonar and propose a data-driven coverage path planning (CPP) method to promote bathymetric mapping with AUVs. The main contributions of this paper include:  
1. The path of the proposed method is intermittently planned based on collected data. The intermittent planner has lower requirement on real-time computing; hence, could be potentially implemented on low size, weight, power and cost (SWaP-C) embedded computers. 2. The path planner uses a new reward function to optimize multiple objectives. The function is designed to account for coverage gain and sonar performance with an additional term to encourage exploring unknown workspace. 3. The reward values for the coverage gain and sonar sensing are computed adaptively. The objective function relies on the predicted sonar swath which is determined based on in-situ measurements instead of a pre-defined constant. The remainder of the paper is organized as follows. In Section 2, we present a review of related work.