Victor R. F. Miranda
Papers
7
Total Citations
226
H-Index
6
About
Victor R. F. Miranda is a robotics researcher whose work centers on autonomous navigation, simultaneous localization and mapping (SLAM), and robotic inspection in challenging environments. He is perhaps best known for developing EKF-LOAM, an adaptive sensor fusion system combining LiDAR SLAM with wheel odometry and inertial data to achieve reliable localization in confined spaces with limited geometric features — a problem that trips up most traditional approaches. With 107 citations, this contribution has become a key reference in robust mobile robot localization. Miranda's broader research portfolio includes the EspeleoRobô project, a robotic platform designed for semi-autonomous inspection of hazardous confined spaces such as caves, pipes, and dam galleries, demonstrating both practical engineering rigor and real-world applicability. His more recent work explores deep reinforcement learning for robotic navigation, showing a capacity to bridge classical robotics with modern machine learning techniques to improve generalization in cluttered, unknown environments. Miranda has also contributed to drone racing autonomy and embeddable navigation modules, reflecting a versatile research vision. Collectively, his work addresses critical safety challenges in industrial and field robotics, making autonomous systems more capable and reliable where human presence is difficult or dangerous.
Research Focus
Key Achievements
Top Papers
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