Ruvita Faurina

Papers

Total Citations

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About

Ruvita Faurina is a researcher specializing in robotics and artificial intelligence, with a particular focus on reinforcement learning applications for autonomous systems. Her most cited work, "ROBOT OBSTACLE AVOIDANCE DENGAN ALGORITMA Q-LEARNING" (2021), demonstrates her significant contribution to the field of mobile robotics. In this study, she designed and implemented a wheeled obstacle avoidance robot prototype using the Q-Learning algorithm, a model-free reinforcement learning technique. The robot was built around an ATMega2560 microcontroller on the Arduino Mega2560 platform, equipped with five HC-SR04 ultrasonic sensors for environmental perception. This work showcases her ability to bridge theoretical machine learning concepts with practical hardware implementation, creating systems that can learn optimal navigation strategies through trial and error. With 2 citations to date, her research provides a foundation for developing intelligent, adaptive robotic systems capable of navigating dynamic environments without human intervention. Faurina's work is particularly valuable for students and researchers interested in embedded systems, sensor integration, and the application of reinforcement learning algorithms to real-world robotic challenges, offering a clear example of how Q-Learning can be effectively deployed on resource-constrained hardware platforms.