Kenta Gunji
Papers
6
Total Citations
19
H-Index
3
About
Kenta Gunji is a robotics researcher whose work sits at the intersection of multi-robot coordination, industrial automation, and spatial AI. His research addresses critical challenges in deploying robots in dynamic, human-centric environments like factories and industrial plants. A standout contribution is his team’s victory in the World Robot Summit 2020 plant disaster prevention challenge, where they coordinated three heterogeneous robot types for inspection, a project that has garnered 5 citations and demonstrates real-world impact. Gunji is also the creator of the LayoutSLAM and LayoutSLAM++ frameworks, which tackle the problem of object map distortion in mobile robotics by leveraging the geometric layout of objects for simultaneous localization and mapping—work that has earned 5 combined citations. More recently, he has pioneered the use of large language models (LLMs) to generate object co-occurrence information, enhancing robots’ spatial understanding of 3D scenes. His additional contributions include novel multi-robot path planning using redundant Voronoi graphs and task scheduling heuristics for garment mass customization. With a growing citation profile and a clear focus on bridging perception, planning, and real-world deployment, Gunji is a rising figure in practical, multi-robot systems.
Research Focus
Key Achievements
Top Papers
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