Yongxing Zhang
Papers
2
Total Citations
7
H-Index
2
About
Yongxing Zhang is a robotics researcher whose work focuses on the kinematics and control of hyper-redundant, bio-inspired robotic systems. His primary research areas include inverse displacement analysis, iterative algorithmic design, and the modeling of continuum-like robots modeled after biological structures such as elephant trunks and bionic trunks. Zhang’s major contributions lie in developing mathematical and computational methods to solve the complex inverse kinematics of hyper-redundant robots composed of serially connected parallel mechanism modules. His 2020 paper on inverse displacement analysis of a bionic trunk-like robot (4 citations) and his 2022 work proposing an iterative algorithm for an elephant’s trunk robot (3 citations) provide foundational approaches for accurately positioning and controlling these highly flexible, multi-degree-of-freedom systems. By treating each parallel module as a geometric line segment and point model, Zhang’s iterative algorithm enables efficient forward approximation and inverse pose adjustment. Though early in its citation impact, his work is significant for advancing the practical deployment of hyper-redundant robots in applications requiring dexterous, snake-like manipulation and navigation in constrained environments.
Research Focus
Key Achievements
Top Papers
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