Fuxing Yang

Beijing University of Posts and Telecommunications

Papers

Total Citations

H-Index

About

Fuxing Yang is a researcher whose work spans robotics, artificial intelligence, and intelligent systems, with a particular focus on optimizing logistics and human-robot interaction. His most significant contribution is in the domain of robotic mobile fulfilment systems (RMFS), where he developed a building-block-based genetic algorithm to solve the robots allocation problem—a critical challenge in e-commerce fulfilment centers like the Kiva system. This work, published in 2019 and garnering 31 citations, has provided a more efficient and flexible approach to order picking, directly impacting warehouse automation. Yang has also advanced 3D action recognition through the introduction of the deep-wide network (DWnet), which achieved 20 citations for its innovative architecture that balances depth and breadth in neural network design. Additionally, his research on convalescent-wheelchair robots, equipped with dynamic absorbers, addresses vibration isolation for patient comfort and safety, contributing to the field of assistive robotics. With a portfolio that bridges theoretical modeling and practical application, Yang’s work continues to influence both academic research and industrial automation, making him a notable figure in the evolution of intelligent robotic systems.