Papers
12
Total Citations
963
H-Index
8
About
Elmar Mair is a robotics researcher whose work spans autonomous aerial vehicles, visual navigation, sensor fusion, and biologically inspired mapping systems. He is perhaps best known for his seminal contribution to autonomous UAV development, with his 2012 paper on indoor and outdoor urban search and rescue platforms accumulating over 800 citations — a testament to its foundational influence on the field of aerial robotics. His research addresses the critical challenge of enabling robotic systems to navigate and operate reliably without external infrastructure such as GPS, making his work especially relevant to disaster response and emergency scenarios. Mair has made significant contributions to IMU-camera calibration and registration, developing spatio-temporal and optimization-based methods that improve the accuracy of inertial-visual sensor fusion in dynamic environments. A distinctive thread running through his work is the development of biologically inspired navigation frameworks, particularly his Landmark-Tree map concept, which draws on theories of insect navigation to create scalable, resource-efficient topological maps suited to platforms with limited computational capacity. His research on visual homing further demonstrates a commitment to elegant, nature-inspired solutions for autonomous robot guidance. Together, these contributions position Mair as an innovative thinker bridging robotics, computer vision, and biological principles.
Research Focus
Key Achievements
Top Papers
- 1
- 2Spatio-temporal initialization for IMU to camera registration56 citations · 2011
- 3
- 4Efficient camera-based pose estimation for real-time applications18 citations · 2009
- 5
- 6Towards efficient and scalable visual homing13 citations · 2018
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- 9
- 10Optimization based IMU camera calibration6 citations · 2011