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About

Rosa Andrie Asmara is a robotics researcher whose work bridges autonomous navigation, intelligent control, and low-cost hardware innovation. Her primary research areas include robot navigation systems, neural network-based control, and sensor development for robotic manipulators. Asmara’s most influential contribution is her HSV-based robot boat navigation system (2020, 24 citations), which demonstrates a practical approach to autonomous maritime navigation without explicit human control. She has also made significant strides in solving inverse kinematics for planar manipulators using Bayesian regularization backpropagation neural networks (2018, 14 citations), offering a robust method for precise robotic arm positioning. Notably, Asmara contributed to accessible robotics through her development of a low-cost 3D-printed robot joint torque sensor (2018, 10 citations), enabling safer human-robot collaboration. Her work on probabilistic localization methods, including a comparative study of discrete Bayes and Kalman filters for 1D robot localization (2019), further showcases her commitment to foundational robotics algorithms. Through her research, Asmara demonstrates a consistent focus on making autonomous systems more intelligent, affordable, and safe—key priorities for the next generation of robotics applications.