Papers

2

Total Citations

13

H-Index

2

About

Lichang Zhao’s research lies at the intersection of autonomous navigation, human-robot interaction, and intelligent product design. Their most cited work, “Multimodal Pedestrian Trajectory Prediction Based on Relative Interactive Spatial-Temporal Graph” (2022, 9 citations), addresses a critical challenge for autonomous vehicles and mobile robots: modeling the inherently random and socially interactive nature of pedestrian movement. By proposing a graph-based framework that captures spatial-temporal interactions, Zhao’s work enhances the safety and predictability of autonomous systems navigating crowded environments. Earlier, Zhao explored the human-centered side of robotics in “Exploring the norms for the UX design of intelligent products: a case study” (2013, 4 citations), using a xylophone-playing robot as a case study to identify key attributes for successful user experience design. This dual focus—bridging technical trajectory prediction with user-centered design principles—demonstrates a holistic approach to robotics and AI. Zhao’s contributions are particularly valuable for researchers developing socially-aware navigation systems and for designers seeking to make intelligent products more intuitive and engaging.

Research Focus

Key Achievements

2
H-Index
2
Papers
13
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Multimodal Pedestrian Trajectory Prediction Based on Relative Interactive Spatial-Temporal Graph
9 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Tiandi Science & Technology (China), Beijing University of Posts and Telecommunications

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago