Papers
4
Total Citations
10
H-Index
2
About
Qi Peng is a researcher at the forefront of robotics and computer vision, whose work bridges the gap between sensing and intelligent perception. His primary research areas include depth estimation, tactile sensing, and object detection for autonomous systems. Peng’s most notable contribution is a novel method for estimating depth maps from any monocular camera using a RealSense camera, a technique that enables robots to acquire critical distance information for tasks like detection and positioning without expensive hardware—a work that has garnered 5 citations. He also designed a flexible capacitive tactile sensor based on Micro-Electro-Mechanical-System (MEMS) technology, creating a sensor array for robotic hand pressure detection, which holds promise for medical and aerospace applications. More recently, Peng has tackled the challenge of deploying Transformer-based end-to-end networks on unmanned aerial vehicles (UAVs), proposing a computationally efficient architecture for aerial image object detection. His earlier work on region-of-interest (ROI) methods for vision robots further demonstrates his commitment to practical, real-time solutions. With a growing citation impact and a focus on enabling robots to see and feel their environment, Qi Peng is a rising voice in intelligent systems engineering.
Research Focus
Key Achievements
Top Papers
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- 4A Practical ROI and Object Detection Method for Vision Robot1 citations · 2020