Chia-How Lin

National Yang Ming Chiao Tung University

Papers

14

Total Citations

232

H-Index

7

About

Chia-How Lin is a robotics researcher whose work spans human-robot interaction, autonomous mobile systems, and affective computing. Best known for pioneering contributions to robotic emotional intelligence, Lin developed innovative frameworks that enable robots to autonomously generate and transition between emotional expressions. His most celebrated work, "Robotic Emotional Expression Generation Based on Mood Transition and Personality Model" (2012, 111 citations), introduced a two-dimensional emotional model integrating robot emotion, mood, and personality — a landmark contribution that significantly advanced socially intelligent robotics. Beyond affective systems, Lin has made meaningful strides in mobile robot perception and safety, developing robust vision-based obstacle avoidance techniques using monocular cameras and inverse perspective transformation. His research also extends to multi-robot cooperation, agent-based control architectures, and smart security systems, including Zigbee sensor network-driven intrusion detection integrated with autonomous robotic response. Throughout his career, Lin has demonstrated a consistent ability to bridge theoretical modeling and practical implementation, producing systems deployable in real-world service and domestic environments. With cumulative citations exceeding 220 across his portfolio, his interdisciplinary contributions — spanning fuzzy-neuro networks, computer vision, and multi-agent systems — mark him as a significant voice in intelligent robotics research.

Research Focus

Key Achievements

7
H-Index
14
Papers
232
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
Robotic Emotional Expression Generation Based on Mood Transition and Personality Model
111 citations · 2012
📈 Most Prolific Year: 2013 (4 Papers)
🤝 Key Collaborators: 19
🏛 Institutions: National Yang Ming Chiao Tung University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago