Jian‐Qiao Sun
Papers
7
Total Citations
132
H-Index
6
About
Jian-Qiao Sun is a distinguished researcher whose work sits at the intersection of robotics, control systems, and computational intelligence. His scholarship spans two principal domains: mobile robot path planning and advanced control of parallel robotic systems, particularly the Delta robot — a mechanically complex, over-actuated platform notorious for its highly nonlinear kinematics and dynamics. Sun has made notable contributions to multi-objective optimization in robotics, applying evolutionary algorithms and cellular automata to solve NP-hard path planning problems, work that has garnered over 60 citations. His more recent focus on data-driven control methods has proven especially impactful: his 2021 paper on neural network-based inverse kinematic control of Delta robots in real-time accumulated 32 citations in just three years, reflecting strong community interest in model-free approaches that eliminate the need for explicit kinematic formulations. This data-driven philosophy extends across his portfolio, encompassing sliding mode control enhanced by neural networks and optimal tracking under unknown system dynamics. With over 130 cumulative citations, Sun's research offers students and practitioners alike a practical roadmap for deploying intelligent, adaptive control strategies in real-world robotic systems where traditional model-based methods fall short.
Research Focus
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Top Papers
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