Ruiqi Cheng

State Key Laboratory of Modern Optical Instruments, Zhejiang A & F University

Papers

Total Citations

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About

Ruiqi Cheng is a researcher at the forefront of assistive technology, specializing in computer vision and sensor fusion to enhance mobility for the visually impaired. His work sits at the intersection of intelligent transportation systems and robotic perception, with a primary focus on developing real-world navigation aids. Cheng’s most cited contribution, "Intersection Perception Through Real-Time Semantic Segmentation to Assist Navigation of Visually Impaired Pedestrians" (2018, 24 citations), tackles a critical challenge in urban mobility: enabling visually impaired pedestrians to safely navigate complex intersections. By leveraging deep learning for semantic segmentation, this work provides a robust, vision-based solution for understanding road geometry and traffic elements, a key component of inclusive smart city infrastructure. In his complementary work, "Low power millimeter wave radar system for the visually impaired" (2019, 7 citations), Cheng explores sensor diversity, designing a compact, energy-efficient K-band FMCW radar system. This prototype demonstrates how low-power radar can reliably detect obstacles, offering a viable alternative to vision-based systems in poor lighting or adverse weather. Together, these contributions showcase Cheng’s commitment to creating practical, multi-modal assistive devices that bridge the gap between cutting-edge robotics and the daily needs of vulnerable road users.