Zunran Wang

Tencent (China), South China University of Technology

Papers

Total Citations

H-Index

About

Zunran Wang is a robotics researcher focused on advancing dynamic manipulation and 3D data processing for autonomous systems. His primary research areas include dual-arm robotic control, nonprehensile manipulation, and point cloud data handling. Wang’s most significant contribution is the development of a unified controller for dual-arm dynamic collaborative manipulation, integrating Time-Optimal Path Parameterization (TOPP) with Model Predictive Control (MPC). This work, published in 2022 and cited 17 times, enables robots to efficiently transport multiple objects without grasping—a critical capability for tasks like warehouse sorting or disaster response. The approach achieves real-time, dynamic coordination between arms, pushing beyond traditional static manipulation. Earlier, Wang explored preprocessing and transmission techniques for 3D point cloud data (2017, 9 citations), addressing challenges in efficient data handling for perception systems. His work bridges theoretical control methods and practical robotic applications, with potential impacts on manufacturing and logistics. Wang’s research demonstrates a commitment to solving complex, real-world manipulation problems through innovative algorithmic design.