Papers
28
Total Citations
122
H-Index
6
About
Yukinori Kakazu is a robotics and artificial intelligence researcher whose work spans autonomous systems, multi-agent coordination, and adaptive robot control. His research contributions address some of the most challenging problems in intelligent robotics, including motion planning for agricultural autonomous vehicles, where his 2003 work introduced a dual-component path planning system capable of optimizing real-world farm navigation. Kakazu has made notable strides in multi-agent systems, exploring group formation behaviors and cooperative motion acquisition for dynamically constrained agents, demonstrating how robots can learn to balance collective optimization tasks through extended stochastic reinforcement learning. His investigations into biologically inspired locomotion — including amoeba-like grouping behaviors and distributed autonomous swimming robots — reflect a commitment to nature-driven design principles. Kakazu also explored human-robot interaction through physiological signal-based adaptive learning interfaces, seeking to personalize machine behavior based on real-time user feedback. Additional work on internet-based robot communication and novel platforms like the flexible Mobile SMA-Net and tensegrity robots illustrates his broad engineering range. With citations accumulated across diverse robotics subfields, Kakazu's portfolio reflects a researcher dedicated to bridging theoretical autonomy with real-world robotic implementation.
Research Focus
Key Achievements
Top Papers
- 1Development of a motion planning system for an agricultural mobile robot9 citations · 2003
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- 4Loose Robot Communication over the Internet8 citations · 2004
- 5Modeling and movement control of Mobile SMA-Net7 citations · 2004
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- 7Adaptive learning interface used physiological signals6 citations · 2002
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- 10Movement Control of Tensegrity Robot.4 citations · 2006