Navyata Sanghvi
Papers
2
Total Citations
9
H-Index
2
About
Navyata Sanghvi’s research lies at the intersection of multi-agent systems, social robotics, and swarm intelligence, with a focus on enabling robots to perceive and interact within complex social environments. Her most notable contribution is the development of the MGpi (Multiagent Group Perception and Interaction) network, a computational deep learning model that allows robots to understand and navigate social dynamics involving multiple agents and groups—a critical step toward socially intelligent human-robot interaction. This work has garnered 5 citations and is recognized for its foundational approach to group perception. Additionally, Sanghvi has explored the vulnerabilities inherent in robotic swarms, particularly in her study on adversarial subversion in coverage tasks (4 citations), where she demonstrated how the very properties that make swarms robust—homogeneity and anonymity—can be exploited. Her research highlights both the promise and the pitfalls of decentralized multi-robot systems, offering insights that are valuable for designing more secure and socially aware autonomous systems. Sanghvi’s work is essential reading for researchers interested in the future of collaborative robotics and human-robot teams.
Research Focus
Key Achievements
Top Papers
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- 2