Pau Segui‐Gasco

Papers

Total Citations

H-Index

About

Pau Segui-Gasco is a researcher specializing in multi-robot systems, with a core focus on decentralized task allocation algorithms. His work addresses the fundamental challenge of efficiently assigning tasks to robots in a way that maximizes overall system utility, a problem of high complexity in robotics and artificial intelligence. His most influential contribution, "Decentralised submodular multi-robot Task Allocation" (2015), with 20 citations, introduces a novel algorithm that enables robots to coordinate and allocate tasks without a central controller, leveraging submodularity to achieve near-optimal solutions. Building on this, his 2019 paper "Sample Greedy Based Task Allocation for Multiple Robot Systems" (9 citations) tackles the computational intractability of task allocation by developing a greedy algorithm that balances solution quality with real-time feasibility. Segui-Gasco's work is notable for its practical approach to a theoretically hard problem, offering scalable solutions that are critical for deploying teams of autonomous robots in dynamic environments. His research has direct implications for applications in search and rescue, warehouse automation, and environmental monitoring, where efficient, decentralized coordination is essential.