Yanfang Zhao
Papers
4
Total Citations
111
H-Index
3
About
Yanfang Zhao is a researcher at the forefront of robotics and computer vision, specializing in autonomous navigation, path planning, and image segmentation under challenging conditions. Her most impactful work, "Path planning for active SLAM based on deep reinforcement learning under unknown environments" (98 citations), introduces a novel framework that enables robots to simultaneously map and localize themselves while intelligently planning trajectories in uncharted, dynamic settings—a critical advance for autonomous systems operating in real-world scenarios. Zhao has also made significant contributions to machine vision, developing an adaptive multi-threshold segmentation algorithm for complex images plagued by unstable lighting and variable workpiece surfaces, a problem common in manufacturing. This work directly addresses the fragility of traditional segmentation methods, enhancing robustness for quality inspection and automated production. Additionally, she has explored bio-inspired optimization for obstacle avoidance, proposing a Variable-dimensional Flower Pollination algorithm for NAO robots navigating dynamic environments. Through her research, Zhao bridges deep reinforcement learning, adaptive vision, and swarm intelligence, offering practical solutions for autonomous robotics in uncertain and industrial settings.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4