Karthikk Subramanian
Papers
1
Total Citations
72
H-Index
1
About
Karthikk Subramanian is a researcher specializing in autonomous navigation, robotics, and the integration of deep learning with classical planning methodologies. His most notable contribution, the 2017 paper "Intention-Net: Integrating Planning and Deep Learning for Goal-Directed Autonomous Navigation," has garnered 72 citations and addresses one of the core challenges in mobile robotics: enabling delivery robots to navigate reliably in unfamiliar environments with minimal prior information. The work introduces a two-level hierarchical framework that elegantly bridges model-free deep learning at the low level with model-based path planning at the high level, allowing robots to make intelligent, goal-directed decisions in dynamic, real-world settings. This hybrid approach reflects a broader trend in robotics research toward combining the adaptability of neural networks with the structured reasoning of traditional planning algorithms. Subramanian's work has made meaningful strides in making autonomous systems more practical and deployable in everyday environments such as office buildings, contributing valuable insights to the fields of robot navigation, human-robot interaction, and intelligent systems design.
Research Focus
Key Achievements
Top Papers
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