Pei‐Han Huang
Papers
1
Total Citations
11
H-Index
1
About
Pei-Han Huang is a robotics researcher specializing in socially aware navigation for mobile robots operating in human-populated environments. Their core contributions lie at the intersection of human trajectory prediction and hybrid sensing, enabling robots to move safely and naturally among crowds. Huang’s most-cited work, "Social crowd navigation of a mobile robot based on human trajectory prediction and hybrid sensing" (2023), has garnered 11 citations, establishing a foundation for integrating predictive models of pedestrian motion with multimodal sensor data to anticipate and avoid collisions. This research addresses a critical challenge in human-robot interaction: ensuring that autonomous systems can interpret and respond to subtle social cues, such as walking paths and personal space, without disrupting natural crowd flow. By advancing hybrid sensing techniques—combining vision, LiDAR, and other inputs—Huang has helped bridge the gap between theoretical motion planning and real-world deployment in crowded spaces like airports, malls, and hospitals. Their work is particularly notable for its practical emphasis on real-time performance and robustness, offering a scalable framework for future service and assistive robots. As social robotics continues to evolve, Huang’s contributions remain essential for creating machines that coexist harmoniously with people.
Research Focus
Key Achievements
Top Papers
- 1