Xunjie Chen

Rutgers, The State University of New Jersey

Papers

Total Citations

H-Index

About

Xunjie Chen is a robotics researcher specializing in bipedal locomotion on complex, deformable terrains. His work bridges computational modeling and control theory to enable stable, energy-efficient walking on challenging surfaces like sand, loose dirt, and moving platforms. Chen’s major contributions include developing the first computational framework for analyzing bipedal walker motion and energy use on granular materials, and creating an enhanced resistive force model that accounts for foot shape-dependent interactions with yielding substrates. These models allow for optimized foot design—demonstrating how shape directly impacts walking efficiency and stability. His most cited paper (4 citations) on energy-efficient foot-shape design for granular terrain introduces a novel optimization approach, while his contingency model predictive control (CMPC) method addresses the underexplored problem of bipedal locomotion on dynamically moving surfaces such as ships and vehicles. Though early in his career, Chen’s focused work on granular terrain locomotion has already attracted attention for its practical implications in field robotics and disaster response. His research stands out for its integration of soil mechanics with control theory, offering a systematic path toward legged robots that can traverse the most challenging natural environments.