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About

Dyah Lestari is a robotics researcher whose work sits at the intersection of autonomous navigation, computer vision, and embedded systems. Her most cited paper, "HSV Based Robot Boat Navigation System" (2020, 24 citations), demonstrates her core contribution: developing practical vision-based control for unmanned surface vehicles. She has advanced the field by integrating color-based object tracking with low-cost hardware, as shown in her work on multi-object tracking for trash-picking robots and connecting Pixy CMUcam5 cameras to Bioloid platforms for robot soccer. Lestari’s research consistently addresses real-world challenges—from maritime patrol and search-and-rescue stabilization to automatic trolleys and path planning using genetic algorithms. Her 2024 paper on MPU6050 modules with ROS and PID control for SAR robots highlights her ongoing focus on robust, real-time control systems. While her citation counts reflect an emerging career, the breadth of her work—spanning surface vehicles, omnidirectional cameras, and obstacle detection—signals a researcher committed to making autonomous systems more accessible and effective in unstructured environments. Her trajectory suggests growing influence in practical robotics applications.