Papers
15
Total Citations
88
H-Index
5
About
Viviana Moya is a robotics and control systems researcher whose work spans teleoperation, human-robot interaction, neural network-based control, and computer vision-driven automation. She has made significant contributions to the field of bilateral teleoperation, developing innovative control schemes for mobile robots, bipedal robots, and humanoid systems that maintain stability and coordination despite real-world challenges such as time-varying delays and asymmetric communication conditions. Her 2024 paper on neural network-based intelligent controllers has rapidly garnered 35 citations, reflecting the immediate impact of her work on adaptive control for nonlinear robotic systems. Moya has also pioneered the integration of EEG-based workload detection into teleoperation frameworks, exploring the human side of robot control in ways that bridge neuroscience and engineering. More recently, she has expanded into deep learning applications, employing YOLO-based algorithms for gesture recognition, object classification, and robotic sorting systems. Her 2025 work on data-driven model predictive control for UAV-manipulator systems further demonstrates her forward-looking research trajectory. With a cumulative citation record reflecting consistent scholarly engagement, Moya represents a versatile and impactful voice in modern robotics research.
Research Focus
Key Achievements
Top Papers
- 1Enhancing Control Systems with Neural Network-Based Intelligent Controllers35 citations · 2024
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- 3Intercontinental Bilateral-by-Phases Teleoperation of a Humanoid Robot6 citations · 2021
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- 8Color Classification Using a 3-DOF Robotic Arm Based on the YOLOv5 Model3 citations · 2024
- 9Color Sorting System Using YOLOv5 for Robotic Mobile Applications3 citations · 2024
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