Shuhao Zhu
Papers
1
Total Citations
2
H-Index
1
About
Shuhao Zhu is a researcher focused on advancing human-robot interaction and autonomous navigation, particularly in crowded, dynamic environments. His most notable contribution is the development of a moving target tracking system for mobile robots based on a modified Social Force Model (SFM). This work addresses the critical challenge of human-robot coexistence by enabling robots to track and follow pedestrians more naturally and safely in congested spaces. By refining the SFM to account for robot motion and pedestrian behavior, Zhu’s approach improves tracking accuracy and collision avoidance, making it highly relevant for service robots, assistive technologies, and collaborative manufacturing. His 2021 paper on this topic has garnered early citations, reflecting its growing influence in the field. Zhu’s research bridges robotics, control theory, and social dynamics, offering practical solutions for real-world deployment. His work is particularly valuable for students and researchers exploring socially-aware navigation and human-robot collaboration, as it provides a robust framework for integrating predictive pedestrian models into robotic systems.
Research Focus
Key Achievements
Top Papers
- 1