Diogo O. Correa

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About

Diogo O. Correa is a researcher in autonomous navigation and intelligent robotics, with a focus on vision-based systems that enable machines to perceive and move through their environments without human intervention. His work centers on integrating artificial neural networks (ANNs) and finite state machines with 3D sensors, such as the Kinect, to create adaptive, real-time navigation solutions. Correa’s most cited paper, “Adaptive finite state machine based visual autonomous navigation system” (2014), has garnered 40 citations, demonstrating its influence in the field of robotic perception and control. In this study, he pioneered a method that dynamically adjusts navigation strategies based on visual input, improving robustness in unstructured settings. His earlier work, “3D Vision-Based Autonomous Navigation System Using ANN and Kinect Sensor” (2012), with 20 citations, laid foundational groundwork by combining depth sensing with neural learning for obstacle avoidance and path planning. Together, these contributions highlight Correa’s role in advancing low-cost, sensor-driven autonomy, making his research particularly relevant for students and engineers developing practical, vision-guided robots for real-world applications.