Zhongliang Jing
Papers
17
Total Citations
338
H-Index
9
About
Zhongliang Jing is a leading researcher at the forefront of soft robotics, visual servoing, and intelligent control systems, with a particular focus on applications in space servicing, aerial manipulation, and underwater exploration. His pioneering work bridges the gap between soft robotic actuation and autonomous vision-based control, enabling robots to operate in unstructured environments without precise calibration. Jing’s most cited paper, “An overview of the configuration and manipulation of soft robotics for on-orbit servicing” (54 citations), establishes foundational knowledge for deploying compliant robots in space. His highly influential “Distance-directed Target Searching for a Deep Visual Servo SMA Driven Soft Robot Using Reinforcement Learning” (50 citations) demonstrates a novel integration of shape memory alloy (SMA) actuators with reinforcement learning for autonomous target acquisition. Jing has also made seminal contributions to uncalibrated visual servoing, as evidenced by his papers on mobile robot control (49 citations) and planar manipulators (41 citations), which eliminate the need for camera calibration—a major practical hurdle. His innovative “Switchable Unmanned Aerial Manipulator System for Window-Cleaning Robot Installation” (47 citations) showcases real-world deployment of aerial robots for high-rise maintenance. With over 300 total citations, Jing’s work on inchworm-snake inspired manipulators and underwater target detection (UUVDNet) continues to push boundaries, making him a key figure in advancing autonomous, soft, and vision-guided robotic systems.
Research Focus
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