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About

Xinming Zhang is a robotics researcher whose work bridges the gap between robotic manipulation, teleoperation, and soft actuation. His key research areas include manipulation planning, whole-body teleoperation, and soft pneumatic actuators. Zhang’s major contributions include developing a goal-conditioned action primitive decomposition and alignment method for manipulation planning from demonstration, which addresses trajectory distribution shifts to adapt prior knowledge to new tasks. He also advanced whole-body teleoperation control for dual-arm robots using sensor fusion, enabling more accurate translation of human arm motions to humanoid robotic arms despite occlusion challenges. Additionally, Zhang designed a self-sensing pneumatic compressing actuator that enhances motion accuracy and load capacity while maintaining the inherent compliance and safety of soft actuators. His work on dynamic cooperative communications with mutual information accumulation for mobile robots in industrial IoT further demonstrates his impact on real-world applications. With over 37 citations across his most-cited papers, Zhang’s research has been published in top venues like *IEEE Robotics and Automation Letters* and *IEEE Internet of Things Journal*. His innovative approaches to hierarchical task decomposition and sensor fusion are shaping the future of autonomous and teleoperated robotic systems.