Papers
16
Total Citations
218
H-Index
8
About
Yoshikazu Arai is a robotics researcher whose work has made significant contributions to the fields of multi-robot systems, autonomous navigation, and collision avoidance. His most recognized achievement is the development of LOCISS (Locally Communicable Infrared Sensory System), an innovative sensor framework enabling autonomous mobile robots to detect one another and surrounding obstacles through infrared local communication. This foundational technology underpins much of his research into adaptive collision avoidance strategies, with his landmark 2002 paper on multilayered reinforcement learning for collision avoidance accumulating 50 citations — a testament to the methodology's influence on the robotics community. Arai's research demonstrates a sophisticated integration of machine learning and hardware engineering. By applying multi-layered reinforcement learning, he addressed the inherently complex decision-making challenges that arise when multiple robots must navigate shared environments simultaneously. His work on absolute position measurement using infrared incident angle detection further expanded the toolkit available for autonomous robot localization. Notably, his research portfolio also extends beyond mobile robotics, with a highly cited contribution to ultra-high precision wafer bonding using surface activated bonding concepts, reflecting impressive interdisciplinary breadth. Collectively, his publications represent a cohesive and impactful body of work spanning over a decade of autonomous systems research.
Research Focus
Key Achievements
Top Papers
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- 7Realization of autonomous navigation in multirobot environment15 citations · 2002
- 8Collision Avoidance in Multi-Robot Environment based on Local Communication.12 citations · 2001
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