Papers
2
Total Citations
32
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2
About
Utkarsh Rai is a researcher at the intersection of robotics, artificial intelligence, and the Internet of Things (IoT), whose work focuses on enabling intelligent, cooperative systems. His primary research areas include multi-robot task allocation, reinforcement learning, and human-robot interaction. Rai’s most impactful contribution is his 2025 paper on "Heterogeneous Multi-robot Task Allocation and Scheduling via Reinforcement Learning," which has already garnered 24 citations. This work addresses the critical challenge of coordinating teams of robots with diverse capabilities to complete spatially distributed tasks efficiently, a problem central to applications in logistics, search-and-rescue, and manufacturing. By framing task allocation as a reinforcement learning problem, Rai’s approach allows robots to learn optimal scheduling policies, significantly improving completion times and resource utilization. Additionally, his earlier 2020 paper on an "IoT based wireless robotic-hand actuation system for mimicking human hand movement" (8 citations) demonstrates his versatility, showcasing a practical system for remote manipulation with applications in surgery and hazardous environments. Rai’s research not only advances theoretical frameworks but also delivers tangible solutions, making him a rising figure in autonomous systems and robotics.
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