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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/16765

Title: Rapid Coverage of Regions of Interest for Environmental Monitoring
Authors: Pinkam, Nantawat
Newaz, Abdullah Al Redwan
Jeong, Sungmoon
Chong, Nak Young
Keywords: Environmental Monitoring
Regions of Interest Coverage
Energy-Effcient Path Planning
Issue Date: 2019-09-20
Publisher: Springer
Magazine name: Intelligent Service Robotics
Volume: 12
Number: 4
Start page: 393
End page: 406
DOI: 10.1007/s11370-019-00290-x
Abstract: We present a framework for rapidly determining regions of interest (ROIs) from an unknown intensity distribution, particularly in radiation fields. The vast majority of studies on area coverage path planning for mobile robots do not investigate the identification of ROIs. In a radiation field, the use of ROIs can limit the required range of exploration and mitigate the monitoring problem. However, considering that an unmanned aerial vehicle (UAV) has limited resources as a mobile measurement system, it is challenging to determine ROIs in unknown radiation fields. Given a target area, we attempt to plan a path that facilitates the localization of ROIs with a single UAV while minimizing the exploration cost. To reduce the complexity of a large-scale environment exploration, entire areas are initially adaptively decomposed using two hierarchical methods based on recursive quadratic subdivision and Voronoi-based subdivision. Once an informative decomposed subarea is selected by maximizing a utility function, the robot heuristically reaches contaminated areas, and a boundary estimation algorithm is adopted to estimate the environmental boundaries. The properties of this boundary estimation algorithm are theoretically analyzed in this paper. Finally, the detailed boundaries of the ROIs of the target area are approximated by ellipses, and a set of procedures are iterated to sequentially cover all areas. The simulation results demonstrate that our framework allows a single UAV to efficiently explore a given target area and maximize the localization rate for ROIs.
Rights: This is the author-created version of Springer, Nantawat Pinkam, Abdullah Al Redwan Newaz, Sungmoon Jeong, Nak Young Chong, Intelligent Service Robotics, 12(4), 2019, 393-406. The original publication is available at www.springerlink.com, http://dx.doi.org/10.1007/s11370-019-00290-x
URI: http://hdl.handle.net/10119/16765
Material Type: author
Appears in Collections:b10-1. 雑誌掲載論文 (Journal Articles)

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