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About

Yongjiang Chen is a robotics researcher whose work centers on the design and control of compliant, adaptive robotic grippers and precision actuation systems. His major contributions lie in developing novel mechanisms and control strategies that enhance the dexterity and force sensitivity of robotic hands. Notably, he introduced a 1-DOF bidirectional graspable finger mechanism for robotic grippers (14 citations), enabling more versatile and adaptive grasping. Chen also advanced actuation technology with a back-drivable linear force actuator for adaptive grasping (15 citations), which allows for safer human-robot interaction. His work on a Bezier-based state calibrating method for low-cost potentiometers (19 citations) addresses the challenge of inherent nonlinearity in sensors, improving the accuracy and reliability of robotic systems. Additionally, his improved rational Bezier model for pneumatic constant force control in robotic polishing (9 citations) tackles hysteretic nonlinearity, enhancing precision in manufacturing applications. With a total of over 57 citations across his key papers, Chen’s research is foundational for developing more intelligent and responsive robotic hands and actuators, with direct implications for industrial automation and assistive robotics.