Tatsushi Nishi
Okayama University, The University of Osaka, Okayama University of Science
Papers
30
Total Citations
397
H-Index
10
About
Tatsushi Nishi is a prominent researcher specializing in robotics, autonomous systems, and manufacturing optimization, with particular expertise in energy-efficient motion planning, multi-robot coordination, and semiconductor manufacturing scheduling. His work spans two decades of sustained contributions that bridge theoretical optimization techniques with practical industrial applications. Nishi's early research established foundational methods for multi-robot route planning, developing distributed Lagrangian decomposition approaches for coordinating automated guided vehicles (AGVs) in semiconductor fabrication environments — work that garnered over 50 citations and influenced subsequent autonomous logistics systems. His later investigation into semiconductor cluster tool scheduling, leveraging Petri Net decomposition for deadlock-free operation, became a key reference in that specialized field with 54 citations. More recently, Nishi has turned his attention toward the energy efficiency imperatives of Industry 5.0, producing highly impactful research applying genetic algorithms, particle swarm optimization, and RRT-based sampling methods to minimize robot energy consumption during motion planning — his 2022 paper on this topic has already attracted 84 citations, his most celebrated work to date. His multi-objective layout optimization for robotic cellular manufacturing further demonstrates his commitment to holistic, industrially relevant solutions. Collectively, his portfolio reflects a researcher consistently pushing the boundaries of intelligent, sustainable automation.
Research Focus
Key Achievements
Top Papers
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- 8An Autonomous Distributed Route Planning Method for Multiple Mobile Robots14 citations · 2003
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