Sina Sharif Mansouri
Papers
15
Total Citations
259
H-Index
8
About
Sina Sharif Mansouri is a robotics researcher whose work sits at the intersection of autonomous aerial systems, subterranean navigation, and multi-robot coordination. He is best known for his pioneering contributions to deploying Micro Aerial Vehicles (MAVs) in challenging, GPS-denied environments, particularly underground mines — a body of work that has earned him over 90 citations on a single landmark 2020 study alone. His research addresses some of the most demanding scenarios in field robotics: enabling MAVs to navigate dark, geometrically complex tunnel networks using visual recognition, convolutional neural networks, and robust localization pipelines. Beyond subterranean settings, Mansouri has made significant strides in infrastructure inspection, developing autonomous aerial frameworks for surveying wind turbines and large-scale 3D structures, demonstrating real-world applicability across industries. His collaborative robotics work spans multi-agent path planning, cooperative 3D coverage, and range-aided relative pose estimation — essential building blocks for deploying robot teams in search-and-rescue and surveillance missions. His 2022 SubT dataset contribution further reflects his commitment to advancing the research community through shared resources. Across more than ten highly cited publications, Mansouri has established himself as a versatile and impactful figure in autonomous aerial robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2Towards Autonomous Surveying of Underground Mine Using MAVs33 citations · 2018
- 3Cooperative coverage for surveillance of 3D structures26 citations · 2017
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- 5Dataset collection from a SubT environment21 citations · 2022
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- 10Multi-Agent Collaborative Path Planning Based on Staying Alive Policy6 citations · 2020