Papers
9
Total Citations
122
H-Index
5
About
Zhendong He is a robotics and artificial intelligence researcher whose work sits at the intersection of autonomous navigation, agricultural robotics, and machine learning. His research focuses primarily on intelligent path planning, computer vision-based crop row recognition, and robot control systems, with particular emphasis on practical applications in smart agriculture. He has made significant contributions to agricultural robot navigation, developing innovative deep learning algorithms such as YOLOv8s-CornNet and ST-YOLOv8s, which enable precise crop row detection across different growth stages of corn — a longstanding challenge in visual navigation for field robots. His 2023 hybrid GJO algorithm for robot path planning has already garnered 55 citations, demonstrating rapid uptake within the robotics community. Beyond agriculture, He has explored biomimetic control strategies, adapting nature-inspired principles into adaptive pure pursuit algorithms for wheeled robots, and pioneered brain-machine interface teleoperation systems using EEG signals. His earlier work on improved Q-learning exploration strategies reflects a sustained interest in reinforcement learning fundamentals. With research spanning autonomous systems, industrial inspection robots, and AI-driven precision agriculture, He represents a versatile and increasingly influential voice in applied robotics research.
Research Focus
Key Achievements
Top Papers
- 1A hybrid strategy-based GJO algorithm for robot path planning55 citations · 2023
- 2
- 3
- 4
- 5
- 6
- 7
- 8Maize Crop Row Recognition Algorithm Based on Improved Unet Network3 citations · 2022
- 9