Papers
6
Total Citations
87
H-Index
4
About
Xuetao Zhang is a robotics researcher whose work pushes the boundaries of autonomous navigation and human-robot collaboration. His primary research areas span visual-inertial odometry, unmanned aerial vehicle (UAV) control, and perception-aware motion planning. Zhang’s major contribution is DVIO, a tightly coupled direct visual-inertial odometry framework that fuses visual and inertial data for real-time state estimation, earning 44 citations since 2020. He has also developed auto-tuning controllers for aggressive rotorcraft transportation tasks and created a human-robot collaboration system designed for high-precision manufacturing, demonstrating his versatility across aerial and industrial robotics. His work on extendable flight systems for commercial UAVs using ROS has provided practical tools for the research community, while his recent topology-guided trajectory generation method addresses the critical challenge of perception-aware navigation without requiring pre-built global maps. With over 87 total citations and publications spanning from 2018 to 2025, Zhang’s research continues to advance the reliability and autonomy of robotic systems in complex, dynamic environments.
Research Focus
Key Achievements
Top Papers
- 1DVIO: An Optimization-Based Tightly Coupled Direct Visual-Inertial Odometry44 citations · 2020
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- 3A Human-Robot Collaboration System towards High Accuracy10 citations · 2020
- 4Extendable Flight System for Commercial UAVs on ROS6 citations · 2018
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