Ming Zhong
Papers
19
Total Citations
256
H-Index
9
About
Ming Zhong is a leading researcher in agricultural and assistive robotics, with a focus on autonomous harvesting, robotic manipulation, and human-robot interaction. His most impactful work includes the development and field evaluation of an autonomous citrus-harvesting robot (48 citations) and a citrus pose estimation system from RGB images (37 citations), addressing critical labor shortages in agriculture. Zhong has also pioneered learning and generalization approaches for service robots using dynamic movement primitives and dynamic potential fields (35 citations), enabling safe obstacle avoidance in unstructured environments. His contributions extend to assistive technologies, including laser-pointer-based grasping for wheelchair-mounted robotic arms (20 citations) and SLAM-based self-calibration of stereo vision systems (23 citations). Notably, his work spans diverse domains, from underwater sea cucumber detection (16 citations) to mushroom picking robots (18 citations), demonstrating versatility in applying robotic perception and control. With over 200 total citations, Zhong’s research is characterized by practical field evaluations and integration of learning from demonstration, making significant strides toward autonomous systems that enhance productivity and quality of life.
Research Focus
Key Achievements
Top Papers
- 1
- 2Citrus pose estimation from an RGB image for automated harvesting37 citations · 2023
- 3
- 4SLAM-Based Self-Calibration of a Binocular Stereo Vision Rig in Real-Time23 citations · 2020
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- 8Underwater sea cucumbers detection based on pruned SSD13 citations · 2019
- 9Learning motion primitives from demonstration10 citations · 2017
- 10