Wei Hong Chin
Papers
13
Total Citations
90
H-Index
5
About
Wei Hong Chin is a robotics researcher specializing in human-robot interaction, assistive robotics, and autonomous navigation, with a particular focus on developing intelligent systems for elderly care and home environments. His major contributions span multiple interconnected domains: real-time affordance detection for ladder climbing robots using dynamic density topological structures (18 citations), episodic memory-based multimodal learning for robot sensorimotor map building and navigation (15 citations), and ecological approaches for object relationship extraction in elderly care robots (9 citations). Chin has also developed lightweight neural networks for fall detection systems (8 citations) and deep learning-based hand gesture communication for social robots (5 citations). His work on interactive information support systems based on informationally structured spaces (13 citations) demonstrates his commitment to community-centric assistive technologies. With over 80 total citations across his publications, Chin's research integrates biologically inspired neural oscillators for quadruped locomotion, incremental episodic memory frameworks for topological mapping, and obstacle prediction networks for safe home-care robot navigation. His innovative use of adaptive resonance theory networks and growing neural gas algorithms has advanced the field of autonomous robot perception and navigation in dynamic, real-world environments.
Research Focus
Key Achievements
Top Papers
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- 6Hand Gesture Communication using Deep Learning based on Relevance Theory5 citations · 2020
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- 9An Incremental Episodic Memory Framework for Topological Map Building3 citations · 2018
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