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About

Dessy Novita is a robotics and autonomous systems researcher whose work sits at the intersection of intelligent robotics, sensor integration, and artificial intelligence. Her research has made significant contributions to medical robotics, particularly in the context of the COVID-19 pandemic, where she developed autonomous navigation systems for hospital robots using 2D LiDAR-based Simultaneous Localization and Mapping (SLAM) and IMU sensor fusion — work that has garnered 10 and 7 citations respectively. These systems address critical real-world challenges, including reducing physical contact between healthcare workers and patients while managing limited personal protective equipment. Beyond medical applications, Novita has explored socially assistive robotics, leveraging convolutional neural networks for object detection and face recognition to enable meaningful human-robot interaction in parental monitoring contexts (5 citations). Her earlier work on extremum seeking algorithms for dead-zone compensation in two-wheeled robots demonstrates a strong foundation in control theory. More recently, she has advanced lightweight obstacle detection systems for mobile platforms, broadening the accessibility of autonomous robotics in healthcare settings. With a growing citation record and interdisciplinary scope, Novita's research offers meaningful solutions to pressing societal challenges through intelligent robotic systems.