Che Liu

Beihang University, University of Toronto

Papers

Total Citations

135

H-Index

About

Che Liu is a pioneering researcher in soft robotics, with a primary focus on stiffness-programmable mechanisms and modular self-reconfigurable systems. His most impactful contribution is the invention of chain-like granular jamming, a novel approach that enables soft robots to achieve instant, large-range stiffness variation—a critical capability for effective environmental interaction. This work, published in 2018, has garnered 123 citations, underscoring its significance in advancing adaptive robotic structures. Liu also explores self-reconfiguration in modular robots, developing parametric L-systems-based modeling frameworks to navigate obstacle environments, though this work has received fewer citations. His 2019 study on rigid-soft coupling structures and stiffness-adjusting devices further demonstrates his commitment to bridging flexibility and rigidity in robotic design. By addressing fundamental challenges in stiffness control and reconfiguration, Liu’s research holds promise for applications in search-and-rescue, medical devices, and adaptive manipulation. His work is particularly notable for its practical approach to enabling soft robots to dynamically tune their mechanical properties, a key step toward more versatile and resilient robotic systems.