Hanyi Li
Papers
9
Total Citations
187
H-Index
6
About
Hanyi Li is a robotics and warehouse automation researcher whose work centers on the design, optimization, and simulation of Robotic Mobile Fulfillment Systems (RMFS) — a cutting-edge paradigm in e-commerce logistics where autonomous robots transport inventory pods to human pickers, rather than the reverse. His most influential contribution, "Introducing Split Orders and Optimizing Operational Policies in Robotic Mobile Fulfillment Systems" (2020, 111 citations), advanced the field by tackling complex order-splitting strategies and operational decision-making that directly improve warehouse throughput and efficiency. Li also developed RAWSim-O, a dedicated simulation framework for RMFS environments, which has become a valuable tool for researchers modeling and benchmarking robotic warehouse operations. His work bridging simulation and real-world deployment demonstrates a rare commitment to translating theoretical findings into practical systems. Beyond fulfillment systems, his earlier research on multi-robot tracking and path planning experimentation established a solid foundation in autonomous robot navigation. With contributions spanning pod repositioning, efficient order picking, and scalable vision-based tracking, Li's body of work has meaningfully shaped how the robotics community approaches the automation of modern warehouse logistics.
Research Focus
Key Achievements
Top Papers
- 1
- 2RAWSim-O: A Simulation Framework for Robotic Mobile Fulfillment Systems19 citations · 2017
- 3From Simulation to Real-World Robotic Mobile Fulfillment Systems11 citations · 2018
- 4RAWSim-O: A Simulation Framework for Robotic Mobile Fulfillment Systems10 citations · 2017
- 5Efficient Order Picking Methods in Robotic Mobile Fulfillment Systems9 citations · 2019
- 6
- 7From Simulation to Real-World Robotic Mobile Fulfillment Systems.6 citations · 2018
- 8
- 9Scalable and flexible vision-based multi-robot tracking system6 citations · 2012