Yuexin Wang

Northwestern Polytechnical University, Longyan University

Papers

Total Citations

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About

Yuexin Wang is a robotics researcher whose work bridges intelligent control, mobile manipulation, and reinforcement learning. Their key contributions center on developing adaptive control strategies for semi-passive and nonholonomic robotic systems, with a particular focus on real-world interaction tasks. Wang’s most cited work, “Walking control of semi-passive robot via a modified Q-learning algorithm” (2024, 5 citations), introduces a novel reinforcement learning approach that enables energy-efficient bipedal locomotion, demonstrating how modified Q-learning can achieve stable walking without complex dynamic models. This work represents a significant step toward more autonomous and adaptable walking robots. Wang’s earlier research, “Research on Visual Servo Grasping of Household Objects for Nonholonomic Mobile Manipulator” (2014, 3 citations), addresses the practical challenge of robotic grasping in domestic environments. By designing an innovative QR-code-based artificial marker system affixed to household objects, Wang enabled nonholonomic mobile manipulators to perform visual servo grasping with improved reliability and precision. This work has implications for assistive robotics and home automation. With a research trajectory spanning from foundational control algorithms to applied manipulation, Yuexin Wang continues to advance the field of intelligent robotics, making contributions that are both theoretically sound and practically relevant for next-generation autonomous systems.