Papers
26
Total Citations
526
H-Index
9
About
Xunyu Zhong is a leading researcher in autonomous robotics, specializing in motion planning, visual servoing, and state estimation for mobile robots and manipulators. His work bridges perception and control, enabling robots to navigate safely in large-scale, dynamic environments. Zhong’s most influential contribution is his hybrid path planning approach, which integrates a Safe A* algorithm with an adaptive window method, amassing 226 citations for its effectiveness in collision-free navigation. He has also pioneered robust visual servo control systems, combining Kalman filtering with neural networks to achieve stable, uncalibrated robotic manipulation—a contribution cited over 60 times. More recently, his LIO-Fusion system (2023) fuses LiDAR, inertial, GNSS, and wheel odometry for reliable 6-DoF estimation, addressing a critical challenge in complex outdoor navigation. Zhong’s work on adaptive obstacle detection using downward-looking LiDAR and pixel-reasoning grasp detection further underscores his impact on practical robotics. With over 450 total citations, his research continues to shape autonomous navigation and robotic manipulation, offering scalable solutions for real-world deployment.
Research Focus
Key Achievements
Top Papers
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- 7Dynamic collision avoidance of mobile robot based on velocity obstacles18 citations · 2011
- 8Adaptive Neuro-Filtering Based Visual Servo Control of a Robotic Manipulator16 citations · 2019
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