Papers
75
Total Citations
9,813
H-Index
35
About
Shaojie Shen is a leading roboticist whose research sits at the intersection of autonomous aerial vehicles, state estimation, and multi-robot systems. Best known for his groundbreaking work on Visual-Inertial Navigation Systems (VINS), Shen has fundamentally advanced how robots perceive and navigate their environments using minimal hardware. His landmark paper, *VINS-Mono* (2018), has amassed over 4,390 citations, establishing a widely adopted framework for robust six-degree-of-freedom state estimation using only a single camera and a low-cost IMU — a contribution that has become a cornerstone reference in mobile robotics and autonomous systems research. Shen's work spans both theoretical foundations and real-world deployment. His early contributions to multi-floor indoor MAV navigation and collaborative ground-aerial robot mapping demonstrated practical autonomy in complex, GPS-denied environments. More recently, his research has pushed the boundaries of UAV exploration efficiency through systems like FUEL and FIESTA, enabling faster, smarter autonomous flight planning. His survey on aerial swarm robotics, cited over 630 times, reflects a broader vision for scalable, coordinated multi-robot systems. Across more than a decade of impactful research, Shen has shaped how the field approaches lightweight, computationally efficient autonomy for aerial platforms.
Research Focus
Key Achievements
Top Papers
- 1VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator4,390 citations · 2018
- 2A Survey on Aerial Swarm Robotics634 citations · 2018
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- 4Autonomous multi-floor indoor navigation with a computationally constrained MAV356 citations · 2011
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- 8Autonomous aerial navigation using monocular visual‐inertial fusion240 citations · 2017
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