Papers
14
Total Citations
193
H-Index
8
About
Erik Blasch is a leading researcher whose work spans computer vision, robotics, and information fusion, with a focus on enabling autonomous systems to perceive and act in complex, real-world environments. His major contributions include pioneering holistic cloud-enabled robotics for real-time video tracking, advancing facial micro-expression recognition through hybrid deep learning models, and surveying emerging neuromorphic dynamic vision sensors that overcome the limitations of traditional cameras. Blasch has also developed innovative 3-D indoor positioning systems using passive radio frequency signals, and applied game-theoretical controls to pursuit–evasion scenarios for ground robots. His work on flexible vision-based navigation for unmanned aerial vehicles, dating back to 1995, laid foundational groundwork for autonomous aerial systems. With over 70 citations on his most-cited paper alone, Blasch’s research has had a significant impact, particularly in enhancing situational awareness through multi-modal sensing and deep learning. His recent contributions to satellite pose estimation using event cameras and smart robot-enabled predictive maintenance further demonstrate his sustained influence. Blasch’s work is notable for its integration of theory and practical hardware-in-loop implementations, making him a key figure in advancing autonomous robotics and intelligent sensing.
Research Focus
Key Achievements
Top Papers
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- 8Autonomy in Use for Information Fusion Systems8 citations · 2018
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