Lucas Figueiredo

Papers

Total Citations

114

H-Index

About

Lucas Figueiredo’s research focuses on multi-robot systems, specifically coverage control and adaptive collaboration in dynamic environments. His major contributions lie in developing algorithms that enable robot teams to autonomously adjust to variations in sensing and actuation performance, ensuring robust coverage even when individual robots degrade or fail. His most cited work, “Adapting to sensing and actuation variations in multi-robot coverage” (2017), has garnered 75 citations and introduces a novel online adaptation framework that allows robots to redistribute their coverage responsibilities in real time. This builds on his earlier 2015 paper (36 citations), which laid the groundwork for performance-adaptive multi-robot coordination. Figueiredo also explores human-robot interaction, as seen in his 2018 work on Voronoi-based coverage control in non-convex environments using virtual reality, where users can intuitively guide robot teams through an immersive interface. His research is highly relevant for applications in disaster response, environmental monitoring, and automated surveillance, where robot teams must operate reliably under unpredictable conditions. With a clear trajectory from foundational theory to practical human-in-the-loop systems, Figueiredo’s work continues to influence the field of adaptive multi-robot coordination.