Vasanth Sarathy
Papers
7
Total Citations
140
H-Index
5
About
Vasanth Sarathy is a researcher at the intersection of cognitive robotics, human-robot interaction (HRI), and artificial intelligence, with a particular focus on enabling robots to navigate the complex social and moral landscape of human environments. His work addresses one of the central challenges in modern robotics: how machines can learn, represent, and apply behavioral norms in dynamic, uncertain real-world contexts. Sarathy has made significant contributions to the DIARC cognitive architecture, a distributed framework integrating cognition, affect, and reflection that has garnered 68 citations and serves as a foundational platform for socially intelligent robots. His research on normative HRI explores how robots can adapt to context-specific human norms, handle exceptions gracefully, and reason about affordances using logic-based frameworks — work that collectively underscores his commitment to commonsense reasoning and safe human-robot collaboration. More recently, Sarathy has explored the frontier of large language models for reinforcement learning, developing LgTS, a system using LLM-generated sub-goals for dynamic task sampling. His evolving interest in human-robot co-creative collaboration signals a broader vision: robots not merely as tools or assistants, but as genuine collaborative partners. For students and researchers in AI and robotics, his body of work offers rigorous, interdisciplinary insights into building machines that are socially aware, ethically grounded, and genuinely useful.
Research Focus
Key Achievements
Top Papers
- 1
- 2Learning behavioral norms in uncertain and changing contexts25 citations · 2017
- 3When Exceptions Are the Norm20 citations · 2019
- 4A Logic-Based Computational Framework for Inferring Cognitive Affordances19 citations · 2016
- 5Enabling Basic Normative HRI in a Cognitive Robotic Architecture5 citations · 2016
- 6
- 7