Chengjun Zhang

Papers

Total Citations

H-Index

About

Chengjun Zhang’s research bridges the frontiers of robotics and flexible electronics, with a focus on novel mechanical design, intelligent control, and advanced sensing. His early work introduced a walking robot based on a 3-RPC parallel mechanism (2011, 10 citations), contributing foundational insights into robotic locomotion. More recently, Zhang has tackled the critical challenge of autonomous navigation in dynamic environments. His 2024 paper on collision avoidance using spiking reinforcement learning (CASRL, 3 citations) proposes an energy-efficient policy for mobile robots with limited onboard computing, addressing a key bottleneck in real-world deployment. Expanding into soft robotics, his 2025 study on liquid metal strain sensors (2 citations) systematically compares microchannel structures, revealing how geometric design directly impacts sensor performance—a nuance often overlooked in the field. Though his citation counts are modest, Zhang’s work demonstrates a deliberate progression from mechanical platforms to intelligent, sensor-rich systems. His integration of bio-inspired spiking neural networks with practical robotics highlights a commitment to both theoretical rigor and hardware feasibility, making his research particularly relevant for students and engineers developing next-generation autonomous robots.