Junxing Yang
Papers
2
Total Citations
30
H-Index
2
About
Junxing Yang has made focused and impactful contributions to the field of mobile robotics, particularly in the critical area of collision avoidance under real-world constraints. His research addresses the fundamental challenge of enabling autonomous robots to navigate safely when they have limited sensing capabilities and incomplete information about both moving obstacles and the surrounding environment. Yang’s most cited work, "Collision Avoidance for Mobile Robots with Limited Sensing and Limited Information about Moving Obstacles" (2017, 23 citations), provides a practical framework for robots to avoid dynamic threats without relying on full environmental knowledge—a key step toward deploying robots in unpredictable, human-populated spaces. An earlier foundational paper (2015, 7 citations) further explores these constraints, establishing a core research thread. By tackling the intersection of sensor limitations and obstacle uncertainty, Yang’s work directly supports the development of safer, more robust autonomous systems. His contributions are particularly valuable for students and researchers working on real-time navigation, sensor fusion, and the practical deployment of mobile robots in complex, dynamic settings.
Research Focus
Key Achievements
Top Papers
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