Papers
8
Total Citations
84
H-Index
4
About
Ash Yaw Sang Wan is a leading researcher in reconfigurable robotics and autonomous complete coverage path planning (CCPP), with a particular focus on service and disinfection robots. Their work addresses the critical challenge of enabling mobile robots to dynamically alter their physical footprint and motion capabilities to navigate both narrow and wide spaces efficiently. Wan’s most influential paper, “Complete coverage path planning for reconfigurable omni-directional mobile robots with varying width using GBNN” (2023), has garnered 35 citations and introduces an adaptive Glasius bio-inspired neural network (aGBNN) approach that significantly reduces computational overhead in complex environments. They also developed a “Waiter Robots Conveying Drinks” system (2020, 18 citations), tackling the practical difficulty of liquid transport in service robotics, and designed a “Reconfigurable Wall Disinfection Robot” (2021, 13 citations) for high-risk public spaces during the COVID-19 pandemic. More recently, Wan has pioneered frameworks for inter-reconfigurable robots, enabling constant-complexity models and multi-robot CCPP solutions for double-pass coverage problems. Their work is widely cited for bridging theoretical path planning with real-world applications in cleaning, inspection, and healthcare, making them a key figure in advancing adaptive, autonomous service robots.
Research Focus
Key Achievements
Top Papers
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- 2Waiter Robots Conveying Drinks18 citations · 2020
- 3Design of a Reconfigurable Wall Disinfection Robot13 citations · 2021
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