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RISS 인기검색어
- 검색키워드
- 저자 : Hiromitsu Fujii (검색결과 2 건)
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Collecting Plant Floor Data using Agent Embedded in Controller
Satoru Hori,Hiromitsu Kato,Hiroshi Fujii,Seiichi Shin 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
In the industrial and robotic fields, equipment manufacturers and system vendors have engaged instandardization activities in order to guarantee interconnection and interoperation and improve productivity andcompetitiveness. Recently, more system flexibility and cost efficiency than before have become necessary due to theintensity of market competition and diversity of customer needs. In plant-floor systems, the need for total costownership reduction has been growing. To meet this need, Japanese organizations use the concept of “Mieruka”, i.e.,visualization, to share and utilize information by making it visible in an easily understandable form. To achieve“Mieruka”, we need to be able to utilize plant-floor level data by flexibly collecting and seamlessly handling the datafrom various devices. We describe our standardization activities in the industrial field, propose a plant-floor level datacollection method using an agent embedded in a controller to flexibly collect data, and discuss an application of thestandardized data model interface that we previously proposed, Super Distributed Objects (SDO), to utilize collecteddata.
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3D Reconstruction of Structures using Spherical Cameras with Small Motion
Sarthak Pathak,Alessandro Moro,Hiromitsu Fujii,Atsushi Yamashita,Hajime Asama 제어로봇시스템학회 2016 제어로봇시스템학회 국제학술대회 논문집 Vol.2016 No.10
In this research, a method for dense 3D reconstruction of structures from small motion of a spherical camera is proposed. Spherical cameras can capture information from all directions enabling measurement of the entire surrounding structure at once. The proposed technique uses two spherical images clicked at slightly displaced positions near the structure, followed by a combination of feature-point matching and dense optical flow. Feature-point matching between two images alone is usually not accurate to give a dense point cloud because of outliers. Moreover, calculation of the epipolar direction with feature point matching is susceptible to noise with small displacements. However, spherical cameras have unique parallax properties allowing use of dense, global information. Taking advantage of this, the global, dense optical flow field is used. The epipolar geometry is densely optimized based on the optical flow field for an accurate 3D reconstruction. A possible use of this research could be to measure large infrastructures (bridges, tunnels, etc.) with minimal robot motion.
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