Qilin Zhang
Papers
2
Total Citations
112
H-Index
2
About
Qilin Zhang is a leading researcher in robotics, computer vision, and human-robot interaction, with a particular focus on autonomous navigation and cognitive workload assessment. His most impactful work, "Convolutional Neural Network-Based Robot Navigation Using Uncalibrated Spherical Images" (2017, 107 citations), pioneered the use of deep learning for vision-based mobile robot navigation, offering a robust alternative to traditional SLAM and lane-detection methods. This contribution has been widely recognized for enabling more flexible and efficient autonomous systems. In parallel, Zhang has advanced the field of human-robotics systems through his work on pilot workload assessment in manned/unmanned-aerial-vehicles teams. His 2017 paper on this topic provides critical methods for evaluating cognitive states, directly informing the design of safer and more intelligent human-robot collaboration frameworks. By bridging deep learning, robotic perception, and cognitive science, Zhang’s research has shaped practical solutions for real-world autonomous systems, making him a key figure in modern robotics and intelligent interaction.
Research Focus
Key Achievements
Top Papers
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- 2