Papers
1
Total Citations
4
H-Index
1
About
Tao Xu is a researcher specializing in visual simultaneous localization and mapping (SLAM), with a focused emphasis on advancing robotic perception and navigation systems. His work tackles some of the most persistent challenges in the field, particularly the degradation of visual tracking performance during rapid, large-angle robotic motion — a critical bottleneck for real-world autonomous systems. His most notable contribution, TKO-SLAM, introduces an innovative approach combining time-delay feature regression with keyframe pose optimization to address trajectory drift and keyframe loss during curved motion sequences. This work demonstrates a sophisticated understanding of both the theoretical underpinnings of visual odometry and the practical demands of deploying robots in dynamic environments. By generating cleaner image frames and preserving keyframe integrity under challenging motion conditions, TKO-SLAM represents a meaningful step forward in making visual SLAM systems more robust and reliable. Though early in citation accumulation with 4 citations since its 2024 publication, the recency of this work suggests its impact is still unfolding. Xu's research sits at the intersection of computer vision, robotics, and spatial intelligence — areas of rapidly growing importance as autonomous systems become increasingly central to modern technology.
Research Focus
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Top Papers
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