Mayank Baranwal

Papers

Total Citations

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About

Mayank Baranwal is an emerging researcher at the intersection of robotics, optimization, and multi-agent systems, with a focused expertise in real-time coordination of autonomous systems. His work tackles one of the most pressing challenges in modern robotics: efficiently allocating tasks among heterogeneous robot teams operating in dynamic, high-stakes environments such as automated warehouses. His paper "Together We Rise: Optimizing Real-Time Multi-Robot Task Allocation using Coordinated Heterogeneous Plays" (2025) demonstrates a sophisticated approach to the multi-robot task allocation (MRTA) problem, leveraging coordinated strategies to maximize productivity in response to the surging demands of e-commerce and online order fulfillment. By designing solutions that account for real-time decision-making under dynamic constraints, Baranwal bridges the gap between theoretical optimization and practical deployment in industrial robotics. Though early in citation accumulation with 2 citations, his 2025 publication signals timely and relevant contributions to a field experiencing rapid growth. His research holds strong implications for the future of warehouse automation, supply chain efficiency, and scalable multi-robot systems, positioning him as a promising voice in autonomous systems research.