Papers
3
Total Citations
7
H-Index
2
About
Masaya Shoji is a robotics researcher focused on enabling autonomous mobile robots to navigate dynamic, unstructured environments—a critical step toward realizing Society 5.0, where humans and machines coexist seamlessly. His work centers on developing perception and control systems that allow robots to act flexibly without prior knowledge or trial-and-error learning. Shoji’s key contributions include a spatial attention-based sensory network that helps robots prioritize relevant environmental cues in real time, and a behavior coordination framework that scales action outputs appropriately in crowded, changing spaces. He also introduced the "Add-if-Silent" rule-based Growing Neural Gas algorithm, which generates high-density topological structures for tracking dynamic objects, advancing how robots perceive moving elements in their surroundings. Though early in his career, with his most-cited papers accumulating 3 and 2 citations respectively, Shoji’s research addresses a fundamental challenge in mobile robotics: achieving human-like adaptability without exhaustive pre-programming. His work has been published in 2022 and 2023, signaling a promising trajectory for practical, real-world robot autonomy.
Research Focus
Key Achievements
Top Papers
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