Yazhou Li

Liaoning Shihua University, Beihang University

Papers

Total Citations

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About

Yazhou Li is a robotics researcher whose work focuses on the intersection of autonomous systems, embedded computing, and intelligent perception. His primary research areas include autonomous navigation, embedded GPU profiling, and deep learning-based object detection for robotic applications. Li’s major contributions center on developing practical, deployable solutions for autonomous machines, particularly in indoor environments. His most cited work, "Design of a Fully Autonomous Indoor Spray Robot" (2023, 6 citations), demonstrates his ability to create complete robotic systems that operate without human intervention. He also made significant technical contributions with "Profiling NVIDIA Jetson Embedded GPU Devices for Autonomous Machines" (2020, 3 citations), which introduced practical profiling methods using tegrastats, jtop, and Nsight Systems to analyze power consumption and CPU/GPU utilization on embedded platforms—critical knowledge for researchers building autonomous vehicles. Additionally, his "RS-RCNN: an indoor window detection algorithm for autonomous spraying robot" (2023, 2 citations) addresses the limitations of traditional CNN-based detection by integrating Swin Transformer with ResNet_50, enhancing spatial awareness for robotic perception. Li’s work bridges the gap between theoretical algorithms and real-world robotic deployment, making him a notable contributor to the growing field of autonomous service robotics.