Nguyen Cong Khoa
Papers
1
Total Citations
2
H-Index
1
About
Dr. Nguyen Cong Khoa is a robotics researcher specializing in sensor fusion, estimation theory, and adaptive filtering for robotic systems. His work focuses on improving the accuracy and reliability of motion estimation in robot arms by integrating data from multiple sensors, particularly MEMS-based inertial measurement units (IMUs) and encoders. His most cited paper, "An Adaptive Filter for IMU/Encoder Data Fusion for Acceleration Estimation in Robot Arms" (2018), introduces a novel adaptive Kalman filter (AKF) that effectively handles noisy and biased sensor measurements. By deriving a discrete-time second-order model, Dr. Khoa’s approach enables precise acceleration estimation, which is critical for advanced robot control and dynamic applications. While his citation count is still growing, his contributions are foundational for researchers working on sensor fusion in robotics, especially in environments where sensor noise and bias pose significant challenges. His work bridges theoretical estimation methods with practical robotic implementations, making it a valuable reference for students and engineers developing robust motion estimation systems.
Research Focus
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Top Papers
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