Teng Ran
Papers
12
Total Citations
220
H-Index
8
About
Teng Ran is a robotics and autonomous systems researcher whose work spans mobile robot navigation, semantic simultaneous localization and mapping (SLAM), and rehabilitation robotics. With a growing body of highly cited publications, Ran has established a strong reputation for advancing intelligent perception and navigation frameworks for robotic systems. Ran's most influential contribution, "Scene Perception Based Visual Navigation of Mobile Robot in Indoor Environment" (2020, 77 citations), laid important groundwork for vision-driven robot autonomy. Building on this, Ran has made significant strides in semantic SLAM, developing probabilistic and Bayesian nonparametric approaches to object association—tackling the notoriously difficult problem of accurate data association in complex, real-world environments. Work on multimodal fusion for autonomous navigation using deep reinforcement learning with sparse rewards further demonstrates Ran's commitment to pushing the boundaries of robot learning under challenging conditions. Notably, Ran also bridges robotics with healthcare, contributing constrained control methods and Udwadia–Kalaba-based trajectory control for lower limb rehabilitation exoskeletons. Across more than ten publications accumulating over 210 citations, Ran's research consistently addresses critical gaps between perception, state estimation, and real-world robotic deployment, making it highly relevant for researchers and students working at the intersection of autonomous systems and intelligent control.
Research Focus
Key Achievements
Top Papers
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- 5Bayesian Nonparametric Object Association for Semantic SLAM15 citations · 2021
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