| Project/Area Number |
18K18427
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 90150:Medical assistive technology-related
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| Research Institution | Gifu University |
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Principal Investigator |
SATO JUNYA 岐阜大学, 工学部, 助教 (20799944)
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| Project Period (FY) |
2018-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2019: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2018: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
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| Keywords | コンピュータビジョン / パターン認識 / 画像処理 / 進化計算 / 人工知能 / Visual odometry / AGV / 全天球カメラ / 画像センシング |
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| Outline of Final Research Achievements |
To promote automation using robots in the medical and welfare field, this study focused on automatic guided vehicle (AGV). It is always necessary to be aware of people and objects around the AGV to drive it safely. Conventionally, multiple cameras and sensors have been required to be installed, however, this has led to high costs. Therefore, this study aims to reduce the cost by using only one omnidirectional camera. In the first year, we surveyed previous researches on self-position estimation, which is necessary for automated driving, and improved existing technologies. In the second year, we investigated whether people and objects can be accurately detected by using deep learning for highly distorted images taken with the omnidirectional camera.
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| Academic Significance and Societal Importance of the Research Achievements |
日本では高齢者人口が急速に増加しているが，介護や介助といった医療福祉関係の人手不足が問題視されている．この問題に注目し，ロボットによる自動化という観点で研究を進めることは社会的に意義がある．また，この問題を解決するために，近年登場した安価で容易に入手可能な全天球カメラを活用し，低コスト化を図ることは学術的に意義があることである．
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