Hirohide Konishi

Papers

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About

Hirohide Konishi is a robotics researcher whose work centers on autonomous mobile robot navigation, with a particular focus on real-time spatial perception and local path planning in unknown environments. His most-cited paper, “Passability-Based Local Planner Using Growing Neural Gas for an Autonomous Mobile Robot” (2024), introduces a novel approach that leverages a growing neural gas algorithm to enable robots to dynamically modify global paths based on 3D perception of their surroundings. This contribution addresses a critical challenge in robotics: allowing autonomous systems to safely navigate cluttered or unpredictable spaces without relying on pre-mapped environments. While his citation count is still growing—with this key paper accumulating 4 citations to date—Konishi’s work represents an important step toward more adaptive and intelligent mobile robots. His research bridges machine learning and robotics, offering practical solutions for real-world deployment in areas such as warehouse logistics, search-and-rescue, and service robotics. As an emerging voice in the field, Konishi is laying the groundwork for robots that can perceive, reason, and act autonomously in complex, unstructured settings.