Tomofumi Fujiwara
Okayama University, Kyoto University, Okayama University of Science
Papers
17
Total Citations
176
H-Index
6
About
Tomofumi Fujiwara is a robotics and automation researcher whose work spans energy-efficient motion planning, rescue robotics, and intelligent manufacturing systems. He has made particularly significant contributions to the optimization of industrial robot operations, with his 2022 study on energy-efficient robot configuration and motion planning using genetic algorithms and particle swarm optimization becoming his most influential work, amassing 84 citations and addressing the emerging demands of Industry 5.0. Building on this foundation, Fujiwara introduced novel sampling-based approaches — including RRT-based schemes — for minimizing energy consumption in robotic pick-and-place tasks, further cementing his expertise in sustainable robotics. Beyond manufacturing optimization, Fujiwara has demonstrated a broad research vision through his development of tough snake robots and multi-limbed rescue platforms such as WAREC-1, contributing to disaster response robotics. His earlier work on 3D scanning, plane detection using RANSAC algorithms, and stereoscopic environmental visualization reflects a sustained interest in robot perception and teleoperation, particularly for hazardous environments. More recently, he has explored surrogate-assisted multi-objective optimization for simultaneous packing and motion planning challenges. Across more than a decade of research, Fujiwara's cumulative contributions position him as a versatile innovator bridging intelligent optimization, human-robot interaction, and applied robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Development of Tough Snake Robot Systems12 citations · 2019
- 4Plane detection to improve 3D scanning speed using RANSAC algorithm11 citations · 2013
- 5
- 6Stereoscopic presentation of 3D scan data obtained by mobile robot7 citations · 2011
- 7
- 8
- 9
- 10