Yanning Zhang

About

Yanning Zhang is a leading researcher in autonomous robot navigation, with a primary focus on vision-based systems for mobile robots and unmanned aerial vehicles (UAVs). Her work addresses critical challenges in enabling robots to navigate complex, low-texture outdoor environments where traditional methods fail. Zhang's most influential contribution is her pioneering use of uncalibrated spherical images combined with convolutional neural networks (CNNs) for robot navigation, as demonstrated in her highly cited 2017 paper (107 citations). This approach bypasses the need for precise camera calibration, making navigation more robust and adaptable. She has also advanced visual odometry for UAVs in feature-poor environments through virtual-real hybrid maps, and developed an innovative infrared camera array system for GPS-denied autolanding of air robots. Her research spans from theoretical frameworks to practical implementations, including autonomous navigation for wheeled robots and quadrotors. With a career marked by creative solutions to real-world robotic challenges, Zhang continues to push the boundaries of autonomous navigation, making her work essential reading for researchers in robotics, computer vision, and intelligent systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Convolutional Neural Network-Based Robot Navigation Using Uncalibrated Spherical Images

   107 citations · 2017
2. 2
   A Monocular Visual Odometry Method Based on Virtual-Real Hybrid Map in Low-Texture Outdoor Environment

   13 citations · 2021
3. 3
   Autonomous Wheeled Robot Navigation with Uncalibrated Spherical Images

   4 citations · 2016
4. 4
   Autonomous Near Ground Quadrone Navigation with Uncalibrated Spherical Images Using Convolutional Neural Networks

   4 citations · 2016
5. 5
   Infrared camera array system for air robot autolanding without GPS

   2 citations · 2016

Key Collaborators

Contact & Links