Ding Liu

Papers

Total Citations

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About

Ding Liu is a robotics researcher whose work focuses on perception and control systems for autonomous mobile robots and manipulators. His key research areas include vision-based environmental perception, intelligent control architectures, and adaptive compensation techniques for robotic systems operating under uncertainty. Liu’s most cited paper, "A High-Precision Vision-Based Mobile Robot Slope Detection Method in Unknown Environment" (2018, 5 citations), introduces a novel approach that uses RGB images to accurately detect slope geometry in unstructured settings—a critical capability for robots navigating uneven terrain. This work addresses the practical challenge of enabling safe, autonomous traversal in unknown environments. His earlier influential study, "Robot manipulator controller based on fuzzy neural and CMAC network" (2004, 3 citations), proposes a hybrid controller that combines a fuzzy neural network with a cerebellar model articulation controller to compensate for dynamic uncertainties in real time. This work showcases Liu’s early contributions to intelligent control, blending neural and fuzzy logic to improve manipulator precision. Together, his research bridges perception and control, offering practical solutions for field robotics and industrial automation.