Peter Negrut
Papers
1
Total Citations
2
H-Index
1
About
Peter Negrut is a researcher at the forefront of space robotics and autonomous planetary exploration, with a primary focus on enhancing lunar perception systems. His most notable contribution is the development of **POLAR-Sim**, a groundbreaking framework that augments NASA’s POLAR (Polar Optical Lunar Analog Reconstruction) dataset. This dataset originally comprised approximately 2,600 pairs of high dynamic range stereo photos captured across 13 varied terrain scenarios—including sparse and dense rock fields, craters, and rocks of differing sizes. Negrut’s work significantly expands this resource, enabling more robust data-driven lunar perception and rover simulation. By improving the fidelity and diversity of training data, his research directly supports the development of safer, more autonomous navigation for future lunar missions. Though early in its citation impact (2 citations in 2025), POLAR-Sim represents a critical step toward reliable AI for extreme environments. Negrut’s work bridges the gap between analog field tests and real-time rover autonomy, positioning him as a key contributor to NASA’s Artemis-era exploration goals.
Research Focus
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Top Papers
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