Sensor Placement for Globally Optimal Coverage of 3D-Embedded Surfaces
Abstract
We carry out a structural and algorithmic study of a mobile sensor coverage optimization problem targeting 2D surfaces embedded in a 3D workspace. The investigated settings model multiple important applications including camera network deployment for surveillance, geological monitoring/survey of 3D terrains, and UVC-based surface disinfection for the prevention of the spread of disease agents (e.g., SARS-CoV-2). Under a unified general "sensor coverage" problem, three concrete formulations are examined, focusing on optimizing visibility, single-best coverage quality, and cumulative quality, respectively. After demonstrating the computational intractability of all these formulations, we describe approximation schemes and mathematical programming models for near-optimally solving them. The effectiveness of our methods is thoroughly evaluated under realistic and practical scenarios.
Keywords
Cite
@article{arxiv.2103.10521,
title = {Sensor Placement for Globally Optimal Coverage of 3D-Embedded Surfaces},
author = {Si Wei Feng and Kai Gao and Jie Gong and Jingjin Yu},
journal= {arXiv preprint arXiv:2103.10521},
year = {2021}
}