Fredric Sanjaya

Papers

Total Citations

H-Index

About

Fredric Sanjaya is a researcher in robotics and human-robot interaction, with a focus on intuitive control systems and gesture recognition. His most cited work, "Body gesture based control system for humanoid robot" (2012), introduces a novel approach using the Fuzzy Neural Generalized Learning Vector Quantization (FNGLVQ) algorithm, achieving an impressive 99.87% accuracy in recognizing 13 distinct human gestures. This contribution has garnered 3 citations, highlighting its niche but significant impact on advancing non-verbal interfaces for humanoid robots. Sanjaya’s research bridges artificial intelligence and robotics, enabling more natural and efficient communication between humans and machines. His work is particularly valuable for developing assistive technologies and autonomous systems where precise, real-time gesture control is critical. By integrating fuzzy neural networks with vector quantization, he has laid groundwork for robust, adaptive control systems that can learn and generalize from limited training data. Sanjaya’s achievements underscore his role in pushing the boundaries of human-robot collaboration, making him a notable figure in the field of intelligent robotics.