Kanak Parmar
Papers
1
Total Citations
7
H-Index
1
About
Dr. Kanak Parmar is a rising star in astrodynamics and autonomous space systems, whose work is forging a new path for robotic exploration in complex orbital environments. Her primary research focuses on spacecraft path-planning within the chaotic, multi-body gravitational dynamics of cislunar space. Dr. Parmar’s major contribution lies in pioneering the use of imitation learning to train autonomous spacecraft. Instead of relying on slow, traditional optimization, her 2023 paper, "Comparison of Learning Spacecraft Path-Planning Solutions from Imitation in Three-Body Dynamics," demonstrates how neural networks can learn generalized, real-time navigation strategies by mimicking expert demonstrations. This approach promises to revolutionize how spacecraft handle the epistemic uncertainty of deep-space missions, enabling them to make rapid, intelligent decisions without constant ground control. With 7 citations in just two years, her work is already gaining traction as a foundational method for next-generation autonomous navigation. By bridging the gap between machine learning and celestial mechanics, Dr. Parmar is not just solving today’s trajectory problems—she is building the cognitive architecture for tomorrow’s resilient, self-driving explorers.
Research Focus
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Top Papers
- 1