Fengji Dai
Papers
1
Total Citations
5
H-Index
1
About
Fengji Dai’s research focuses on autonomous navigation and motion planning for wheeled mobile robots, with a particular emphasis on safe and efficient operation in dynamic, real-world environments. His most-cited work, “Trend-aware motion planning for wheeled mobile robots operating in dynamic environments” (2020), addresses a critical limitation in conventional trajectory generation: the assumption that dynamic obstacles can be treated as static. By incorporating obstacle motion trends into the planning process, Dai’s approach enables robots to anticipate and react to moving objects, significantly improving collision avoidance in cluttered, unpredictable settings. This contribution has earned 5 citations and represents a meaningful step toward more intelligent, context-aware robotic navigation. Dai’s work bridges the gap between theoretical planning algorithms and practical deployment, offering solutions that are both computationally efficient and robust to real-world uncertainties. His research is particularly relevant for applications in autonomous logistics, service robotics, and industrial automation, where robots must share space with humans and other moving agents. Through his trend-aware methodology, Dai continues to advance the field of mobile robotics, making autonomous systems safer and more reliable in dynamic environments.
Research Focus
Key Achievements
Top Papers
- 1