Yaniel Carreno

Papers

Total Citations

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About

Yaniel Carreno is a robotics researcher whose work advances the frontier of autonomous multi-robot systems, with a particular focus on underwater and offshore missions. His key research areas include heterogeneous multi-robot coordination, temporal planning, and goal allocation strategies for complex, resource-constrained environments. Carreno’s major contribution lies in developing a decentralised framework that integrates goal distribution with temporal planning, enabling fleets of diverse autonomous underwater vehicles (AUVs) to collaboratively manage dynamic missions—such as persistent offshore infrastructure supervision—without relying on a central controller. His most cited work, "A Decentralised Strategy for Heterogeneous AUV Missions via Goal Distribution and Temporal Planning" (2020, 20 citations), demonstrates how this approach can generate feasible plans that respect individual robot capabilities and task requirements, a critical step toward practical persistent autonomy. Additional influential papers (each with 9 citations) further refine task allocation strategies for heterogeneous teams in offshore settings, addressing the scalability limitations of traditional temporal AI planners. Carreno’s research is notable for bridging theoretical planning algorithms with real-world marine applications, offering a scalable solution for autonomous ocean monitoring and inspection. His work continues to shape the development of resilient, decentralised multi-robot systems for challenging operational domains.