Julian Chang

Chien Hsin University of Science and Technology

Papers

Total Citations

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About

Julian Chang is a roboticist whose research spans cable-driven parallel robots, pneumatic actuation systems, and bipedal locomotion. His most cited work, "Design and implementation of a multi-degrees-of-freedom cable-driven parallel robot with gripper" (2018, 16 citations), addresses a key challenge in robotics: creating systems with large workspaces, high payload-to-weight ratios, and low inertia. By developing a cable-driven parallel robot with a gripper, Chang demonstrated how controlled cables acting in parallel on an end-effector can outperform traditional rigid-link manipulators in specific applications. Earlier, he tackled complex control problems with a pneumatic cart-seesaw system (2007, 6 citations), a super articulated mechanical system requiring novel stabilization and equilibrium control. Chang also contributed to humanoid robotics through his work on bipedal stair-climbing (2010, 6 citations), where he employed a fuzzy stabilization tuning approach to simplify the computationally intensive Zero-Moment Point (ZMP) method. This work eliminated the need for complex dynamic modeling while maintaining stable gait. Chang’s research consistently focuses on making advanced robotic systems more practical and accessible, from cable-driven manipulators to walking robots, with an emphasis on control innovation and mechanical design.