Papers
22
Total Citations
281
H-Index
7
About
Jingdong Zhao is a leading researcher in robotic manipulation, focusing on anthropomorphic hand design, redundant manipulator control, and intelligent assembly. His seminal 2009 work on an underactuated robot hand controlled by electromyographic (EMG) signals, cited 137 times, pioneered bio-inspired grasping that adapts to human intent. Zhao has made critical contributions to solving inverse kinematics for redundant robots, developing collision-avoidance algorithms for dynamic environments (2021, 21 citations) and real-time motion planning for non-holonomic systems (2022, 6 citations). His research on time-jerk optimal trajectory planning using augmented Lagrange constrained particle swarm optimization (2017, 16 citations) and sequential quadratic programming (2017, 7 citations) enhances robot efficiency and smoothness. In precision assembly, Zhao introduced a learning-based two-stage method for submillimeter insertion tasks using only visual inputs (2023, 19 citations), addressing uncertainties in sensor and robot systems. His work on multifingered dynamic grasping with three-axis tactile feedback (2014, 10 citations) and actuation configuration via postural synergies (2017, 7 citations) advances dexterous manipulation. Zhao also tackles space robotics, achieving high-precision trajectory tracking for space manipulators (2023, 13 citations). With over 240 citations across his portfolio, Zhao’s innovations in underactuated mechanisms, kinematic optimization, and learning-based control are shaping next-generation robotic hands and autonomous assembly systems.
Research Focus
Key Achievements
Top Papers
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- 4Time-jerk optimal trajectory planning of a 7-DOF redundant robot16 citations · 2017
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