Zhu Yichen
Papers
1
Total Citations
11
H-Index
1
About
Zhu Yichen is a robotics researcher whose work focuses on reactive obstacle avoidance and motion prediction for autonomous systems operating in dynamic environments. His key research areas include mobile robot navigation, collision avoidance algorithms, and trajectory prediction. His most notable contribution is the development of the Dynamic Window with Virtual Goal (DW-VG) approach, a novel reactive obstacle avoidance method that integrates a debounce filter with polynomial curve-fitting to predict obstacle trajectories in real time. This work, published in 2019, has garnered 11 citations and addresses a critical challenge in robotics: enabling robots to navigate safely among moving obstacles without relying on pre-mapped environments. By introducing a virtual goal strategy within the dynamic window framework, Zhu’s method enhances decision-making speed and reliability, making it particularly valuable for applications in autonomous vehicles, service robots, and drone swarms. His research bridges the gap between reactive control and predictive planning, offering a practical solution for real-world deployment. Zhu Yichen’s work continues to influence the development of safer, more adaptive robotic systems, and his DW-VG algorithm stands as a foundational step toward fully autonomous navigation in unpredictable settings.
Research Focus
Key Achievements
Top Papers
- 1