Guozhang Jiang
Papers
34
Total Citations
1,057
H-Index
16
About
Guozhang Jiang is a prominent robotics researcher whose work spans intelligent robot control, force sensing, grasp planning, and autonomous navigation. Based at the intersection of mechanical engineering and artificial intelligence, Jiang has made significant contributions to advancing robotic systems for manufacturing, medical, and rehabilitation applications. Among his most influential contributions is his pioneering work on fiber Bragg grating (FBG)-based force sensors, including a three-dimensional plantar force sensor (143 citations) and a six-dimensional force/torque sensor with low coupling (104 citations), both designed to enhance robot dexterity and precision. His 2022 paper on genetic algorithm-based trajectory optimization for digital twin robots has rapidly gained traction with 156 citations, reflecting the growing importance of intelligent path planning in smart manufacturing. Jiang has also advanced robotic grasping through probability-based grasp planning for medical robotics (92 citations) and comprehensive reviews of multi-fingered robotic hand optimization. His explorations into SLAM-based navigation, sEMG-driven human-computer interaction for rehabilitation robots, and deep learning-integrated mapping further demonstrate his breadth. With over 800 cumulative citations, Jiang's research meaningfully bridges theoretical robotics and real-world intelligent automation systems.
Research Focus
Key Achievements
Top Papers
- 1Genetic Algorithm-Based Trajectory Optimization for Digital Twin Robots156 citations · 2022
- 2A Three-Dimensional Fiber Bragg Grating Force Sensor for Robot143 citations · 2018
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- 4Probability analysis for grasp planning facing the field of medical robotics92 citations · 2019
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- 8Optimal grasp planning of multi-fingered robotic hands: a review52 citations · 2015
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- 10Multi-Objective Location and Mapping Based on Deep Learning and Visual Slam32 citations · 2022