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About

Koki Ozasa is a robotics researcher whose work centers on autonomous mobile robots and their ability to perceive and navigate three-dimensional spaces. His primary research areas include 3D space perception, traversability analysis, and local path planning, with a particular focus on the use of Growing Neural Gas (GNG) algorithms for real-time environmental understanding. Ozasa’s most-cited paper, "Growing Neural Gas with Different Topologies for 3D Space Perception" (2022, 20 citations), introduces a novel approach to enabling robots to detect and estimate the 3D pose of target objects in unknown environments. He further developed this line of research in "Growing Neural Gas based Traversability Clustering for an Autonomous Robot" (2023, 7 citations), which addresses how robots can recognize traversable terrain from 3D point cloud data, constrained by their physical embodiment. His 2024 work on a passability-based local planner demonstrates his ongoing contributions to adaptive navigation. With a total of 37 citations across his most-cited papers, Ozasa’s research is steadily gaining recognition for its practical applications in autonomous robotics, particularly in enabling robots to operate safely and effectively in unstructured, unknown environments.