• The Journal of Korea Robotics Society
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• v.5 no.1
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• pp.41-47
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• 2010

This paper proposes a path planning method of a mobile robot in two-dimensional work space. The path planning method is based on a cell decomposition approach. To create a path which consists of a number of line segments, the Delaunay Triangulation algorithm is used. Using the cells produced by the Delaunay Triangulation algorithm, a mesh generation algorithm connects the starting position to the goal position. Dijkstra algorithm is used to find the shortest distance path. Greedy algorithm optimizes the path by deleting the path segments which detours without collision with obstacles.

• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.505-513
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• 2017

Recently, numerous small area estimation studies have been conducted to obtain more detailed and accurate estimation results. Most of these studies have employed spatial regression models, which require a clear definition of spatial neighborhoods. In this study, we introduce the Delaunay triangulation as a method to define spatial neighborhood, and compare this method with the k-nearest neighbor method. A simulation was conducted to determine which of the two methods is more efficient in defining spatial neighborhood, and we demonstrate the performance of the proposed method using a land price data.