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Multi-Robot Coverage Path Planning in 3-Dimensional Environments

Nikolaos Baras, Minas Dasygenis, Νικόλαος Πλόσκας

Year
2019
Citations
4

Abstract

Unmanned Vehicles are being used in several application domains, such as mapping, agriculture, and surveillance. In these application domains, the problem of finding a path that covers the entire Area of Interest (AoI) in a predefined environment is known as Coverage Path Planning (CPP). Even though many works have been focused on solving the CPP problem in 2D environments, the CPP problem in 3D environments has not attracted considerable attention. In this paper, we propose an algorithm capable of solving the CPP problem both in 2D and 3D environments. The algorithm can utilize multiple robots tailoring the coverage path for each robot based on its specifications, i.e., speed and type. We have performed an experimental evaluation of the algorithm in artificially synthetic environments and report the results.

Keywords

Motion planningComputer scienceRobotPath (computing)Mobile robotReal-time computingDistributed computingArtificial intelligenceComputer network

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