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About

Yiheng Chen is a leading researcher in the field of soft robotics and intelligent control, with a primary focus on pneumatic artificial muscle (PAM) actuated systems. His work addresses critical challenges in developing compliant, safe robots for human-robot interaction, particularly in rehabilitation and exoskeleton applications. Chen's major contributions include pioneering energy-based motion control and neuroadaptive control methods for PAM robots, which overcome inherent difficulties like high nonlinearity, hysteresis, and input uncertainties. His highly cited 2021 paper on energy-based motion control (80 citations) established a foundational framework for stable, compliant actuation. Chen has also advanced the practical deployment of these systems through learning-based error-constrained control for exoskeleton robots and hardware-validated experiments. Beyond traditional PAM research, he has innovated in edible soft robotics, designing and characterizing candy-based actuators (32 citations), and developed soluble polymer pneumatic networks to improve the accessibility and durability of soft robotic actuators. With over 250 total citations, Chen's work bridges theoretical control advances with tangible hardware demonstrations, making significant strides toward safer, more adaptable robotic systems for rehabilitation and assistive technologies.