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About

Yau-Zen Chang has made significant contributions to the fields of robotics, motion planning, and control systems, with a particular focus on autonomous mobile robots and flexible manipulators. His most impactful work, "Practical and flexible path planning for car-like mobile robot using maximal-curvature cubic spiral" (2005, 63 citations), introduced an innovative approach to generating smooth, feasible trajectories for non-holonomic vehicles, addressing a fundamental challenge in autonomous navigation. Chang’s early research on "On the adaptive control of flexible joint robots" (1992, 41 citations) laid critical groundwork for handling the complex dynamics of elastic robotic systems, influencing subsequent developments in adaptive control theory. His comparative study of evolutionary multi-objective optimization for smooth path planning (2007, 18 citations) advanced the use of computational intelligence in robotics, enabling efficient collision-free navigation in static environments. Chang also developed a simple yet effective fuzzy motion planning strategy for autonomous mobile robots in unknown indoor spaces (2007, 9 citations), demonstrating that low-cost systems can achieve sophisticated behaviors. His later work on simulation-based collision detection for scaled polyhedral objects (2014, 5 citations) and hybrid optimization methods for hexapedal robot gaits (2010, 2 citations) further showcases his versatility in tackling both theoretical and practical robotics challenges. With over 138 total citations across his key publications, Chang’s research continues to inspire advances in autonomous navigation and robot control.