Vina Wahyuni Eka Putranti

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About

Vina Wahyuni Eka Putranti is a researcher focused on advancing industrial robotic vision, with a particular emphasis on cost-effective 3D object pose estimation. Her key research areas include computer vision, optimization algorithms, and robotics, where she addresses the critical challenge of enabling robots to accurately perceive and interact with objects using affordable hardware. Her most notable work, "Optimization Estimating 3D Object Pose Using Levenberg-Marquardt Method" (2019), introduces a novel approach to improving pose estimation accuracy through the Levenberg-Marquardt optimization technique, specifically designed for mono vision cameras to minimize system costs. This contribution is foundational for future developments in robot control movement for object grasping, bridging the gap between low-cost sensing and high-precision robotics. While her citation count is currently modest, the practical implications of her research for industrial automation—particularly in reducing hardware expenses without sacrificing performance—highlight its potential for significant real-world impact. Her work represents a valuable step toward making advanced robotic vision systems more accessible and efficient for manufacturing and logistics applications.