Ryosuke Ooe

Hokkaido University of Science, Hokkaido University

Papers

Total Citations

H-Index

About

Ryosuke Ooe is a researcher focused on advancing autonomous robotic systems through artificial intelligence and virtual simulation. His work spans two key areas: acoustic event recognition for disaster response robotics and virtual robot behavior acquisition. In his 2015 paper on acoustic events recognition, Ooe introduced a deep learning-based approach to classify and recognize sounds in noisy environments, enabling multiple autonomous robots to respond effectively to acoustic cues during disaster scenarios. This work, with 2 citations, addresses critical challenges in real-world robotic deployment. Earlier, in 2010, Ooe developed a design tool for autonomous virtual robots that can learn behaviors independently within a three-dimensional physically modeled environment, incorporating an approximate fluid dynamics model. This foundational research, also cited 2 times, demonstrates his commitment to bridging simulation and reality for robotic autonomy. Ooe’s contributions highlight the integration of deep learning and virtual environments to create more adaptive, intelligent robotic systems, offering valuable insights for researchers in robotics, AI, and human-robot interaction.