Akira Oyama
Papers
6
Total Citations
29
H-Index
3
About
Akira Oyama is a robotics researcher whose work bridges the gap between infrastructure inspection and human-robot interaction. His primary research areas include pipeline inspection robotics, computer vision, and natural language understanding for service robots. Oyama's most significant contributions lie in developing earthworm-inspired robots for sewer pipe inspection, where he pioneered methods for three-dimensional mapping from internal pipe images and deep learning-based rust detection. His 2019 paper on 3D pipeline mapping using earthworm robots has garnered 11 citations, establishing foundational work in this domain. More recently, Oyama has focused on exophora resolution—enabling robots to understand ambiguous instructions containing demonstratives like "that one." His 2023 paper on multimodal exophora resolution (8 citations) and the 2024 ECRAP system demonstrate innovative approaches to combining visual and linguistic information for robot action planning. His latest 2025 work tackles the challenging problem of resolving references to objects outside the robot's field of view through interactive questioning. Oyama's research has practical implications for aging infrastructure maintenance and assistive robotics in home environments.
Research Focus
Key Achievements
Top Papers
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- 3Detection of Rust from Images in Pipes Using Deep Learning4 citations · 2021
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