Papers
3
Total Citations
28
H-Index
2
About
Bruna Guterres is a robotics researcher whose work bridges industrial automation and intelligent control systems. Her primary research areas include autonomous welding robotics, human-robot interaction, and deep reinforcement learning for mobile robot navigation. Guterres made significant early contributions to industrial robotics through her highly cited 2017 study on seam tracking and welding bead geometry analysis for autonomous welding robots (22 citations), addressing critical challenges in hazardous shipbuilding environments by reducing human intervention. She further advanced human-robot collaboration in welding processes through semiotics-based interface design (2019), applying sign theory to improve teleoperation efficiency. Her most recent work (2024) explores deep reinforcement learning for enhancing generalization in both aerial and terrestrial mobile robot control, introducing delayed policy learning to improve autonomous mapless navigation. This research demonstrates her evolution from traditional industrial robotics toward cutting-edge AI-driven autonomous systems. With a career spanning foundational industrial applications to emerging DRL methodologies, Guterres exemplifies the modern robotics researcher who bridges practical manufacturing challenges with sophisticated artificial intelligence solutions, contributing to safer, more efficient robotic systems across multiple domains.
Research Focus
Key Achievements
Top Papers
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- 3Semiotics Applied to Human-Robot Interaction in Welding Processes2 citations · 2019