Byron Hernandez

Technological University of Pereira, University of Florida

Papers

Total Citations

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About

Byron Hernandez is a robotics researcher focused on the intersection of autonomous navigation, agricultural technology, and human-robot safety. His work centers on developing intelligent systems that enable robots to perceive, plan, and act in complex, real-world environments. Hernandez’s most influential contribution is his comprehensive review of path planning and control for autonomous robots (14 citations), which systematically evaluates techniques like A*, Probabilistic Roadmaps, and Genetic Algorithms for mobile robot applications. This foundational work has guided subsequent research in autonomous navigation. More recently, he has advanced agricultural robotics by applying Vision Transformers for multi-object tracking (2024, 4 citations), enabling precise spatial association in dynamic field environments. His development of a CNN-based cascade estimator for robot end-effector pose estimation (2023, 2 citations) directly addresses the critical need for accurate robot localization in collaborative settings, enhancing safety for human coworkers. By bridging classical motion planning with modern deep learning approaches, Hernandez is shaping the future of autonomous systems that can safely and efficiently operate alongside humans in industries ranging from manufacturing to agriculture.