Cheng Cao

Papers

Total Citations

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About

Cheng Cao’s research focuses on the intersection of rehabilitation robotics and intelligent control systems, with a particular emphasis on obstacle-avoidance algorithms for lower-limb rehabilitation robots. Their major contributions lie in developing novel control methods that enable omnidirectional rehabilitation robots to navigate complex environments safely and effectively. Cao’s work integrates neural networks and fuzzy control techniques to create algorithms that can detect obstacle boundaries, generate environmental attributes, and perform fuzzy matching with knowledge bases to achieve real-time obstacle avoidance. This approach represents an important advancement in making rehabilitation robots more autonomous and safer for patient use. Among their most cited works, “Research on Obstacle-Avoidance Control Algorithm of Rehabilitation Robot Combined with Neural Network” (2010, 5 citations) and “Research on Obstacle-Avoidance Control Algorithm of Lower Limbs Rehabilitation Robot Based on Fuzzy Control” (2009, 4 citations) demonstrate their pioneering efforts in applying intelligent control to assistive robotics. While the citation counts reflect the specialized nature of this emerging field, Cao’s work has laid foundational groundwork for subsequent developments in rehabilitation robot navigation, contributing to the broader goal of creating more responsive and adaptive assistive technologies for individuals with mobility impairments.