K. V. Prashanth
Papers
1
Total Citations
11
H-Index
1
About
K. V. Prashanth is a leading researcher at the intersection of machine learning, autonomous systems, and intelligent navigation. His work focuses on developing informed machine learning techniques that empower autonomous agents to operate reliably in complex, real-world environments. His most-cited paper, "Empowering autonomous indoor navigation with informed machine learning techniques" (2023), has garnered 11 citations and exemplifies his approach of integrating domain knowledge with data-driven models to enhance decision-making in robotics and navigation. Prashanth’s contributions are particularly impactful in the field of indoor navigation, where he addresses challenges such as sensor noise, dynamic obstacles, and energy efficiency. His research bridges theoretical advances in reinforcement learning and practical deployment in autonomous vehicles and drones. With a growing citation footprint, Prashanth is recognized for his ability to translate algorithmic innovations into robust, real-world applications. His work not only advances the state of the art in autonomous navigation but also provides a blueprint for developing intelligent systems that can learn and adapt in unstructured environments.
Research Focus
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Top Papers
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