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About

Zikang Shi is an emerging researcher specializing in robotic machining, motion control, and kinematic calibration, with a particular focus on five-axis hybrid machining robots and CNC toolpath optimization. His work addresses fundamental challenges in manufacturing automation, bridging the gap between theoretical robotics and high-precision industrial applications. Shi's most significant contributions lie in toolpath smoothing methodologies for hybrid machining robots. His 2023 papers — collectively accumulating nearly 40 citations — introduced analytical C3-continuous smoothing algorithms that reduce curvature discontinuities and synchronize motion across robotic axes, directly improving machining efficiency and surface quality. His 2024 work on real-time interpolation with low-pass filtering further refined motion control for five-axis systems, while his tool orientation optimization research advances kinematic performance in ball-end milling operations. Beyond toolpath planning, Shi has made notable strides in kinematic calibration, proposing compact multi-DOF joint models for parallel robots and a lightweight calibration framework for heavy-load mobile robotic systems — including specialized neutron diffraction applications. With over 60 cumulative citations across a compact publication window of just two years, Shi demonstrates rapid, high-impact growth as a contributor to precision robotics and advanced manufacturing research.