Zushun Chen
Papers
2
Total Citations
4
H-Index
2
About
Zushun Chen is a pioneering researcher in intelligent robotics, with a focus on autonomous navigation and manipulator motion planning in unknown environments. His work bridges fuzzy logic control and sensor-based obstacle modeling to enable robots to operate safely and adaptively without pre-mapped surroundings. In his 1996 paper, Chen introduced a fuzzy logic-based behavior fusion system for mobile robot navigation, allowing multiple behavioral commands—such as obstacle avoidance and goal-seeking—to be smoothly integrated for real-time decision-making. This early work laid the groundwork for more adaptive robotic control. His 2002 contribution advanced manipulator motion planning by presenting an efficient algorithm for sensor-based obstacle modeling directly in configuration space. By defining fundamental obstacles in the workspace and mapping them rapidly, Chen enabled robotic arms to avoid collisions in dynamic, unknown environments. Though his citation counts are modest, his work represents foundational steps in merging fuzzy logic with geometric reasoning for practical robotics. Chen’s research remains relevant for engineers developing autonomous systems that must navigate or manipulate objects in unstructured settings.
Research Focus
Key Achievements
Top Papers
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