Neta Larasati

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About

Neta Larasati is a researcher in mobile robotics and intelligent control systems, with a primary focus on autonomous navigation and object-following mechanisms. Her most-cited work, "Object Following Design for a Mobile Robot using Neural Network" (2017, 13 citations), addresses a fundamental challenge in mobile robot design: enabling robots to safely navigate and track targets using sensor-based neural network approaches. Larasati’s contributions center on developing efficient, real-time methods for object detection and path planning, emphasizing the integration of neural networks to enhance a robot’s ability to move through dynamic environments without relying on predefined maps. This work has practical implications for service robotics, autonomous vehicles, and industrial automation. While her citation count reflects a growing interest in her research, Larasati’s focus on bridging neural network techniques with practical robot navigation problems marks her as a promising contributor to the field. Her research is particularly relevant for students and engineers seeking to understand how machine learning can improve autonomous systems’ responsiveness and safety in unstructured settings.