Jingqi Ma

Guangdong Institute of Intelligent Manufacturing

Papers

Total Citations

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About

Jingqi Ma’s research lies at the intersection of human-robot interaction and intelligent control systems, with a focus on gesture recognition and autonomous navigation. In a widely noted 2021 study, Ma introduced a gesture recognition method based on the YOLOv4 network, addressing long-standing challenges such as gesture similarity and occlusion. This work has significant implications for collaborative robotics and smart home control, where intuitive, real-time interaction is essential. Earlier, in 2017, Ma tackled the problem of mobile robot path planning in complex environments by developing a fuzzy control algorithm. This approach enhanced a robot’s ability to navigate dynamically and safely, contributing to the broader field of autonomous systems. Although Ma’s citation counts are modest, the work demonstrates a clear trajectory from foundational navigation algorithms to advanced deep learning-based interaction. Ma’s contributions are particularly valuable for researchers exploring the integration of computer vision and robotics, offering practical solutions that bridge theoretical control methods with modern neural network architectures.