Chin Wei Hong
Papers
5
Total Citations
26
H-Index
2
About
Chin Wei Hong is a robotics researcher whose work sits at the intersection of robot perception, bio-inspired locomotion, and human-robot interaction. His primary research areas include grasp affordance detection, neural locomotion control, and spatial attention-based navigation for mobile robots. Hong’s most cited work, “Real-time Grasp Affordance Detection of Unknown Object for Robot-Human Interaction” (2019, 11 citations), introduces a vision-depth sensor fusion approach that outputs a seven-dimensional gripping pose for hand-over tasks, a critical contribution to safe and intuitive human-robot collaboration. He also developed a muscle-reflex model of the Felidae family’s forelimb and hindlimb (2020, 9 citations), integrating central pattern generators with reflex circuits to inspire more dynamic legged robot controllers. More recently, Hong has explored topological mapping and fuzzy motion planning, proposing cognitive architectures that mimic hippocampal place cell learning for incremental map building. His work on spatial attention-based sensory networks (2022) aims to enable mobile robots to navigate dynamic environments without prior knowledge, advancing the vision of an ultra-smart society. With a growing citation record and a focus on bridging biological inspiration with robotic implementation, Hong is establishing himself as a thoughtful contributor to embodied intelligence and autonomous systems.
Research Focus
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Top Papers
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