Weidong Yang

Fudan University, University of Science and Technology Beijing

Papers

Total Citations

H-Index

About

Weidong Yang is a researcher whose work bridges robotics, computer vision, and cognitive systems. His research spans two interconnected domains: the development of intelligent robotic perception and the modeling of biologically inspired cognitive architectures for autonomous systems. In the realm of computer vision, Yang has contributed to advancing robotic environmental understanding through the creation of specialized datasets, most notably the DOS Dataset (2023), a novel benchmark designed to enable deformable object segmentation for sweeping robots — a challenging problem with significant practical implications for domestic robotics. His earlier work demonstrates a longstanding interest in how robots process and respond to sensory information, exemplified by his 2015 study proposing a cognitive model for robotic sensorimotor systems. Grounded in Skinner's operant conditioning principles, this model integrates cerebellum, basal ganglia, and cerebral cortex components to replicate biological sensorimotor mapping — a thoughtful effort to close the gap between neuroscience and robotics engineering. While his citation record reflects an emerging body of work, Yang's research touches on foundational questions in embodied AI and autonomous robot intelligence, making his contributions a meaningful reference point for researchers working at the intersection of cognitive modeling and robotic perception.