A Novel Data-Driven Visualization and Analysis Framework for Embedded Robotic Firmware
Elia Yermakov, Maysoon Ghandour, Hang Su, Samer Alfayad · 2025
The growing complexity of embedded firmware in robotics and automation, including mobile robots, industrial actuators, and autonomous systems, presents significant challenges related to maintainability, debugging, and efficient developer onboarding. Traditional documentation methods frequently become outdated and insufficient, which complicates code comprehension and increases the likelihood of errors. At the same time, current tools often provide only static or fragmented documentation without the interactive, realtime insights required for effective development. To address these limitations, we present a unified visualization and documentation approach based on the open-source tools Doxygen and Graphviz. When applied to a sophisticated embedded control board designed for robotic applications, this method generates interactive documentation, call graphs, and module dependency diagrams that enhance code comprehension, simplify debugging, and accelerate onboarding. In addition, the integration supports targeted optimization by highlighting performance bottlenecks and areas of excessive code complexity, thereby guiding data-driven refactoring. Overall, our findings demonstrate that automated, interactive visualization significantly improves maintainability and development efficiency in embedded software.