Worked on enhancing the perception robustness of the technolojin/autoware.universe repository, focusing on the autoware_euclidean_cluster component. Addressed a critical edge case by implementing a C++ fix that ensures the perception module continues to publish detections even when the input point cloud is empty. This change prevents loss of detections and reduces the risk of downstream failures, thereby improving the reliability of autonomous operation in robotics applications. Maintained code quality and traceability through signed-off commits and alignment with pull request workflows. Demonstrated expertise in C++ programming, perception systems, and robotics while contributing to the stability of the perception pipeline.