Margarita Rebolledo
Papers
2
Total Citations
12
H-Index
2
About
Margarita Rebolledo is a rising figure in evolutionary robotics, whose work tackles the critical challenge of making autonomous robots both capable and energy-efficient. Her research focuses on the co-optimization of task performance and energy consumption, a largely overlooked but vital aspect for real-world deployment. In her 2022 paper, she demonstrated that robots can be evolved to achieve high task proficiency while dramatically reducing their power draw, addressing a key bottleneck in long-duration autonomy. Rebolledo also advanced the field’s methodological toolkit with her 2020 work on parallelized Bayesian optimization, which significantly accelerates the evolution of expensive robot controllers—a contribution that has already garnered 7 citations. By bridging the gap between theoretical optimization and practical energy constraints, her work lays the groundwork for sustainable, self-sufficient robotic systems. Though early in her career, Rebolledo’s focus on energy-aware design positions her as a researcher to watch, with her insights poised to influence everything from search-and-rescue bots to planetary rovers.
Research Focus
Key Achievements
Top Papers
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