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About

Zhengtao Liu is a robotics researcher whose work sits at the intersection of perception, locomotion, and autonomy for mobile robots operating in unstructured environments. His primary research areas include dynamic visual SLAM, wheel-leg transformable robot design, and terrain-adaptive locomotion. Liu’s major contributions include developing a robust visual SLAM system that fuses panoptic segmentation with geometric information to enable reliable robot mapping in dynamic environments—a critical advancement over traditional static-scene SLAM. He is also the lead designer of SWhegPro, a novel wheel-leg transformable robot capable of shifting between wheel, e-shape leg, and S-shape leg morphologies, enabling swift and robust locomotion under heavy payloads. To address the challenge of terrain awareness, Liu pioneered sound-based terrain classification for multi-modal robots and proposed a unified contact parameter estimation method for locomotion on deformable granular terrains. His work on a hybrid wheel-leg transformable robot with minimal actuator realization demonstrates his commitment to simplifying complex designs without sacrificing versatility. With his most cited papers accumulating over 29 citations since 2022, Liu is establishing himself as a rising figure in field robotics, pushing the boundaries of how robots perceive and move through the real world.