Luiza de Macedo Mourelle
Papers
21
Total Citations
350
H-Index
11
About
Luiza de Macedo Mourelle is a Brazilian researcher whose work spans swarm robotics, computational intelligence, and hardware implementation of neural networks. She has made particularly significant contributions to the field of swarm robotic systems, addressing fundamental challenges in distributed localization, dynamic task allocation, and simultaneous localization and mapping (SLAM). Her research consistently applies nature-inspired algorithms — including Particle Swarm Optimization (PSO) and genetic algorithms — to solve complex, real-world coordination problems in multi-robot environments, with her 2015 work on distributed localization earning over 50 citations and her PSO-based task allocation framework attracting 45 citations, reflecting the broad influence of her approaches. Beyond robotics, Mourelle has contributed to the hardware design of artificial neural networks, developing a dynamic MAC-based architecture for FPGA implementation (44 citations), demonstrating her range across both software and hardware domains. Her co-authorship of *Fuzzy Systems Engineering: Theory and Practice* (2005, 36 citations) further underscores her foundational contributions to soft computing theory. More recently, her 2021 work on communication optimization in swarm robotics signals continued relevance in an evolving field. Collectively, her portfolio reflects a career dedicated to making distributed intelligent systems more efficient, resilient, and practically deployable.
Research Focus
Key Achievements
Top Papers
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- 4Fuzzy Systems Engineering: Theory and Practice36 citations · 2005
- 5Simultaneous localization and mapping using swarm intelligence based methods28 citations · 2020
- 6Distributed and resilient localization algorithm for Swarm Robotic Systems21 citations · 2016
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