Yang Gao

About

Yang Gao is a robotics researcher whose work centers on mobile robot autonomy, with particular expertise in path planning, localization, and environmental perception. His research addresses one of the core challenges in autonomous robotics: enabling mobile robots to navigate reliably and safely in complex, dynamic environments. Gao's most influential contribution lies in bridging the gap between path planning and localizability — the capacity of a robot to accurately determine its position. His 2019 paper, "A New Path Evaluation Method for Path Planning With Localizability" (16 citations), introduced a novel framework that incorporates localization reliability directly into path selection, significantly reducing navigation risk. This work was complemented by deep learning-based approaches to predicting localizability, published in 2020, demonstrating his commitment to integrating modern machine learning techniques into classical robotics problems. Earlier in his career, Gao made foundational contributions to dynamic environment navigation, developing collision prediction methods using adaptive Kalman filtering and particle filter-based path planning approaches. His fan-shaped grid mapping algorithm offered an innovative geometric approach to global path planning in known environments. With publications spanning over a decade and accumulating more than 50 citations, Gao's body of work reflects a sustained and evolving research agenda that remains highly relevant to the advancement of reliable, intelligent mobile robot systems.

Research Focus

Key Achievements

Top Papers

1. 1
   A New Path Evaluation Method for Path Planning With Localizability

   16 citations · 2019
2. 2
   A Prediction Method of Localizability Based on Deep Learning

   8 citations · 2020
3. 3
   An online path planning approach of mobile robot based on particle filter

   8 citations · 2013
4. 4
   A Collision Predict Based Local Path Planning of Mobile Robots

   7 citations · 2009
5. 5
   Fan-shaped Grid Based Global Path Planning for Mobile Robot

   4 citations · 2010
6. 6
   Global Path Planning of Mobile Robot Based on Particle Filter

   3 citations · 2009
7. 7
   Local Path Planning of Mobile Robots in Dynamic Unknown Environment Based on Prediction of Collision

   3 citations · 2009
8. 8
   Localizability of Laser SLAM Robot Based on Deep Learning

   1 citations · 2019

Key Collaborators

Contact & Links