Manuel Carrera
Papers
2
Total Citations
7
H-Index
1
About
Manuel Carrera is a visionary researcher at the intersection of aerospace engineering and human-machine interaction, whose work is redefining how humans operate in extreme environments. His primary research areas include autonomous navigation for space exploration, soft robotics for physiological support, and advanced telepresence systems. Carrera’s most notable contribution is his pioneering work on "Adaptive Navigation for Lunar Surface Operations Using Deep Learning and Holographic Telepresence" (2022, 6 citations), which tackles the critical challenge of guiding astronauts through the visually impoverished terrain of the lunar South Pole. By integrating deep learning with holographic cues, he provides a solution to navigation deficits caused by low solar angles and permanently shadowed regions. More recently, Carrera has advanced wearable technology with his 2025 paper on "Utilizing Closed-Loop Physiological Feedback for Dynamic Compression in Soft Robotic Wearables" (1 citation), addressing orthostatic intolerance in pilots and astronauts through real-time, adaptive compression. This work promises to mitigate blood pooling and hypotension during high-G maneuvers and post-mission recovery. Carrera’s research stands at the forefront of creating safer, more intuitive tools for space exploration and human performance, marking him as a key innovator in his field.
Research Focus
Key Achievements
Top Papers
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- 2