Area Partition for Coastal Regions with Multiple UAS

Article · April 2017with47 Reads
DOI: 10.1007/s10846-017-0559-9
Abstract
The paper presents a novel algorithmic approach that allows to tackle in a common framework the problems of area decomposition, partition and coverage for multiple heterogeneous Unmanned Aircraft Systems (UAS). The approach combines computational geometry techniques and graph search algorithms in a multi-UAS context. Even though literature provides several strategies for area decomposition like grid overlay decomposition or exact cellular methods, some fail to either successfully decompose complex areas, or the associated path generation strategies are not feasible. The proposed approach manages to perform an exact cellular decomposition of non-convex polygonal coastal areas and includes an attributes based schema for area partitioning. In particular, the proposed solution uses a Constrained Delaunay Triangulation (CDT) for computing a configuration space of a complex area containing obstacles. The cell size of each produced triangle is constrained to the maximum projected Field-of-View (FoV) of the sensor on-board each UAS. In addition, the resulting mesh is considered as an undirected graph, where each vertex has several attributes used for area partitioning and coverage in a multi-UAS context. Simulation results show how the algorithms can compute sound solutions in real complex coastal regions.
    • These missions are often handled by the means of a grid decomposition of areas in order to accomplish complete coverage[11], for instance in crop spraying or aerial photography. As we've shown in previous studies[12][18], complex scenarios and geographic attributes are not treated properly by the use of a simple grid decomposition of an area. More specifically, coastal area tasks with their numerous no fly zones or complex shores, impose a dynamical approach which has been developed in the context of the MarineUAS project.In a test case scenario area as seen inFig.4,
    [Show abstract] [Hide abstract] ABSTRACT: Unmanned Aerial Systems (UAS) integration to future airspace is one of the greatest challenges in Air Traffic Management. The use of UAS for covering wide areas implies the consideration of airspace restrictions and static and dynamic obstacle avoidance. This results in complex shapes that need to be partitioned adequately to ensure coverage. Another important element for consideration in the generation of safe and efficient trajectories of UAS is the wind field. Typically, in severe wind scenarios, wind is considered often a hazardous condition. However, recent studies show that proper identification of the wind field could be used to increase the energy efficiency of the mission. This paper presents a novel method of area decomposition and partition that ensures coverage by generating a triangular mesh to optimize the coverage in the presence of urban areas, airspace restrictions or even the presence of an obstacle. The waypoint sequencing considers the wind field in order to perform on-line adjustments to ensure energy gains or to minimize energy losses with the identified wind field. For this purpose, an innovative method for wind identification is proposed which analyses the statistical behavior of wind vector estimates in order to identify specific features and characterize given models. Given the design philosophy and architecture, this system can be integrated into next generation autonomous UAS flight management systems as part of the waypoint sequencing and trajectory optimization functions. A test case in the north-Seattle area is presented, which is simulated using a 6DOF model with different wind scenarios which resulted into considerable energy gains either by heeding the wind field during the waypoint sequencing and during the mission execution. Results show that there is a significant improvement on the energy efficiency with an energy consumption reduced by 10% in the presence of wind.
    Full-text · Conference Paper · Jun 2017
    • This strategy is applied either in a continuous space or in a square grid decomposition overlay. However, complete coverage is not always achieved and usually simple non convex areas are chosen as a test case[9]. In case of non convex areas, the usual strategy is decomposing that region into a sum of convex polygons.
    Conference Paper · Jun 2017
Project
MarineUAS is an EU-funded doctoral program to strategically strengthen research training on Autonomous Unmanned Aerial Systems for Marine and Coastal Monitoring. It is a comprehensive researcher tr…" [more]
Conference Paper
July 2016
    Several approaches can be identified in the literature for area decomposition: Grid based methods, Cellular decomposition and Boustrophedon (or Morse) decomposition. This paper proposes a novel discretization method for the area based on computational geometry approaches. By using a Constrained Delaunay Triangulation, a complex area is segmented in cells which have the size of the projected... [Show full abstract]
    Article
    April 2017 · Sensors · Impact Factor: 2.25
      This paper tackles the problems of exact cell decomposition and partitioning of a coastal region for a team of heterogeneous Unmanned Aerial Vehicles (UAVs) with an approach that takes into account the field of view or sensing radius of the sensors on-board. An initial sensor-based exact cell decomposition of the area aids in the partitioning process, which is performed in two steps. In the... [Show full abstract]
      Conference Paper
      June 2017
        Unmanned Aerial Systems (UAS) integration to future airspace is one of the greatest challenges in Air Traffic Management. The use of UAS for covering wide areas implies the consideration of airspace restrictions and static and dynamic obstacle avoidance. This results in complex shapes that need to be partitioned adequately to ensure coverage. Another important element for consideration in the... [Show full abstract]
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