Papers
5
Total Citations
140
H-Index
4
About
Guangyi Chen is a leading researcher at the intersection of robotics, computer vision, and autonomous navigation, with a focus on enabling intelligent systems to perceive, plan, and act in complex, dynamic environments. His work is pivotal in advancing both the theoretical foundations and practical applications of mobile robotics and agricultural automation. Chen’s most impactful contribution is a two-layer path-planning method that synergizes a Particle Swarm Optimization (PSO)-enhanced Artificial Potential Field (APF) with a fuzzy-based Dynamic Window Approach (DWA), a work that has garnered over 100 citations for its effectiveness in navigating mobile robots through multi-obstacle settings. He has also made significant strides in agricultural robotics, authoring a highly-cited review on vision-based apple-harvesting robots that systematically analyzes fruit recognition and picking-pose algorithms. Further demonstrating his breadth, Chen has developed novel computer-vision techniques for weed recognition, specifically for identifying dandelions, and has explored counterfactual analysis for predicting human trajectories in autonomous vehicle contexts. His recent work also surveys the development of express sorting robots, underscoring his commitment to solving real-world logistical challenges. With a publication record spanning high-impact venues, Chen’s research continues to shape the future of intelligent, autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4Human Trajectory Prediction via Counterfactual Analysis6 citations · 2021
- 5Research Status and Development of Express Sorting Robots2 citations · 2023