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About

Vrushabh Zinage is a robotics researcher focused on the critical challenge of safe, scalable, and deadlock-free multi-agent navigation. His work addresses the fundamental tension between ensuring safety guarantees and achieving efficient coordination in decentralized robotic systems, particularly in constrained environments like doorways and intersections. Zinage's major contributions include developing novel approaches using discrete-time control barrier functions that enable multiple robots to navigate social mini-games without collisions or deadlocks, while respecting actuation limits and scaling to thousands of agents. His most cited paper (2025, 6 citations) presents a framework for deadlock-free navigation in social mini-games, while his work on decentralized control under limited actuation (2025, 5 citations) addresses the practical constraints of real-world deployment. Zinage has also pioneered TransformerMPC (2024-2025, 6 combined citations), an innovative method that leverages transformer attention mechanisms to accelerate model predictive control for real-time robotic applications. His research bridges theoretical guarantees with practical scalability, offering solutions that are both provably safe and computationally efficient for next-generation multi-robot systems operating in human environments.