Tomoharu Ohsumi
Papers
1
Total Citations
2
H-Index
1
About
Tomoharu Ohsumi is a robotics researcher whose work lies at the intersection of computer vision, neural networks, and robotic manipulation. His key contributions focus on enhancing visual perception for precise robot positioning tasks, particularly through innovative structured lighting techniques. In his most cited work, "Structured lighting to enhance global image feature sensitivity in a neural network based robot-positioning task" (2002), Ohsumi introduced a novel method for extracting global image descriptors by projecting a grid pattern onto target surfaces. This approach artificially created robust visual features, enabling a 5-DOF robot arm to achieve more accurate positioning through neural network-based control. While his citation count of 2 reflects a niche but foundational contribution, the work demonstrates early promise in bridging structured illumination with machine learning for robotic vision—a concept that has since gained traction in industrial automation and 3D sensing. Ohsumi’s research offers valuable insights for students and researchers exploring sensor fusion, feature engineering, and the integration of classical vision techniques with modern neural architectures in robotics.
Research Focus
Key Achievements
Top Papers
- 1