Yangqing Wang
Papers
1
Total Citations
5
H-Index
1
About
Yangqing Wang is a robotics researcher whose work centers on motion planning and control for wheeled mobile robots operating in complex, dynamic environments. His most-cited paper, "Trend-aware motion planning for wheeled mobile robots operating in dynamic environments" (2020, 5 citations), introduces a novel approach that moves beyond traditional static obstacle avoidance by incorporating the predicted motion trends of dynamic obstacles. This contribution addresses a critical gap in trajectory generation, enabling safer and more efficient navigation in real-world settings where obstacles are not stationary. Wang’s research is particularly valuable for applications in autonomous logistics, service robotics, and intelligent transportation, where robots must adapt to unpredictable human and vehicular movements. While his citation count reflects an emerging career, the conceptual innovation of trend-aware planning marks him as a promising voice in the field. His work challenges conventional static-map assumptions, offering a more realistic framework for robot autonomy. For students and researchers interested in the intersection of robotics, artificial intelligence, and real-time decision-making, Wang’s research provides a forward-looking perspective on how robots can intelligently share space with moving agents.
Research Focus
Key Achievements
Top Papers
- 1