Max Robotics — Global Service Robot Directory + US Certification

About

Yuqing Liu’s research lies at the intersection of haptics, rehabilitation robotics, and autonomous systems, with a growing focus on explainable AI and physics-informed machine learning. Liu’s early work includes the design and calibration of a novel 6-degree-of-freedom haptic device (27 citations), which advanced force feedback for teleoperation and virtual environments. In rehabilitation robotics, Liu developed a scenario interaction system using Unity3D and Kinect to enhance patient-robot engagement. More recently, Liu has pioneered robot state estimation using physics-informed neural networks and multimodal proprioceptive data, eliminating the need for external contact sensors—a breakthrough for legged robots. Complementing this, Liu introduced a novel explainable AI framework for situation recognition in autonomous robots, addressing the critical challenge of partial unlabeled data. This work bridges the gap between deep learning performance and interpretability, a key concern for safety-critical applications. With a career spanning haptic device engineering, cognitive task analysis for space teleoperation, and cutting-edge AI for robotics, Liu’s contributions are shaping more intuitive, resilient, and transparent robotic systems.