Papers
1
Total Citations
3
H-Index
1
About
Chao Pan is a researcher in robotics and optimization, with a focus on trajectory planning for articulated mechanical systems. Their key contributions lie in developing efficient motion control strategies for six-degree-of-freedom (6-DOF) manipulators, particularly through the integration of time-separating techniques with improved particle swarm optimization (PSO) algorithms. In their notable 2017 work, Pan introduced a method that transforms key robot postures from a linkable model into joint space values, enabling smoother and more efficient trajectory generation. This approach addresses critical challenges in industrial automation, such as reducing computational complexity and enhancing operational speed. Although their most-cited paper has garnered 3 citations, Pan’s work represents a foundational step in bridging heuristic optimization with practical robotic control, offering a scalable framework for real-time applications. Their research is particularly relevant for students and engineers seeking to understand how metaheuristic algorithms can be tailored for kinematic constraints in manufacturing and assembly tasks. Pan’s contributions underscore the ongoing effort to make robotic systems more adaptive and energy-efficient.
Research Focus
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Top Papers
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