Deepak Viswanathan
Papers
1
Total Citations
10
H-Index
1
About
Deepak Viswanathan is a leading researcher in human-aware navigation for social robotics, with a primary focus on integrating perception uncertainty into autonomous systems. His most influential work, "Incorporating perception uncertainty in human-aware navigation: A comparative study" (2016, 10 citations), introduces a probabilistic framework that models the uncertainty inherent in robotic perception and examines its impact on social navigation performance. By extending the social costmap model around humans, Viswanathan demonstrates how accounting for perceptual noise can significantly improve the safety and naturalness of robot movements in crowded environments. This contribution bridges the gap between theoretical navigation algorithms and real-world deployment, where sensors are imperfect and human behavior is unpredictable. His research has been instrumental in advancing human-robot interaction, particularly in developing robots that can navigate seamlessly alongside people in public spaces, hospitals, and homes. Viswanathan's work is widely recognized for its practical implications, offering a robust foundation for future studies in socially-aware robotics and autonomous systems.
Research Focus
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Top Papers
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