Yen-Ching Chang

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About

Yen-Ching Chang is a researcher specializing in intelligent control systems and mobile robotics, with a particular focus on motion planning, navigation, and position estimation. Her major contributions include the development of a particle swarm optimization (PSO)-based method for the optimal design of PID controllers, enabling a two-wheeled mobile robot to navigate autonomously from an initial to a desired configuration in unknown, obstacle-filled environments. This work, published in 2013, has garnered 11 citations, reflecting its relevance in the field of autonomous robotics. Additionally, Chang advanced localization techniques by demonstrating how a laser range finder and four artificial reflectors can accurately determine a mobile robot’s position in three-dimensional space, using a PSO algorithm to enhance precision. This 2011 study, with 3 citations, underscores her innovative application of swarm intelligence to real-world robotic challenges. Chang’s research bridges theoretical optimization algorithms and practical robotic systems, offering valuable insights for students and researchers in robotics, control engineering, and artificial intelligence. Her work exemplifies the effective integration of computational intelligence into autonomous navigation.