G. Saritha

Papers

Total Citations

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About

G. Saritha is a researcher at the intersection of geospatial engineering, robotics, and machine learning. Her work bridges the physical and digital worlds, with a primary focus on terrain mapping and autonomous systems. Saritha’s most cited paper, “Digital elevation model and terrain mapping using LiDAR” (2021, 41 citations), establishes her as a key contributor to high-precision environmental sensing, enabling more accurate topographical analysis for applications in surveying and infrastructure planning. She extends this technical expertise into robotics with her 2022 work, “Machine Learning Based Approach to Predict the Position of Robot and its Application” (23 citations), which introduces a self-adjusting framework inspired by pendulum dynamics. This innovative approach allows robots to fine-tune their own settings, enhancing adaptability and stability in real-time operations—a significant step forward for modern mechanical technology. By integrating machine learning with classical physics principles, Saritha demonstrates how autonomous systems can achieve greater resilience through internal self-correction cycles. Her work holds promise for advancing robotic autonomy in unstructured environments, making her a notable voice in the growing field of intelligent, self-optimizing machinery.