Papers
22
Total Citations
498
H-Index
12
About
Siddharth Mayya is a robotics researcher whose work sits at the intersection of multi-robot systems, swarm intelligence, and decentralized control. His research spans coverage control, task allocation, localization, and the principled design of collective behaviors in robot swarms — including those operating under severe size and sensing constraints. Mayya's most impactful contribution is his involvement in the Robotarium project, a freely accessible, remotely operated multi-robot testbed that has democratized experimental robotics research worldwide, accumulating over 211 citations. He has also advanced decentralized coverage control strategies, including a minimum-energy approach for time-varying environments and a graph neural network-based framework that enables robots with limited sensing to coordinate effectively. Perhaps most creatively, his early work reframed inter-robot collisions not as failures but as a viable sensing and information modality in densely packed micro-robot swarms — a conceptual shift that opens new design possibilities for miniaturized systems. Across task allocation, heterogeneous sensor fusion for target tracking, and set-theoretic multi-task prioritization, Mayya consistently bridges rigorous theory with real-world implementation. With cumulative citations exceeding 400, his contributions are shaping how researchers think about scalable, resource-constrained autonomy in multi-robot systems.
Research Focus
Key Achievements
Top Papers
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- 4Closed-loop task allocation in robot swarms using inter-robot encounters24 citations · 2019
- 5Coverage Control in Multi-Robot Systems via Graph Neural Networks22 citations · 2022
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- 8The Robotarium: Automation of a Remotely Accessible, Multi-Robot Testbed20 citations · 2021
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- 10A Set-Theoretic Approach to Multi-Task Execution and Prioritization16 citations · 2020