March 2025 monthly summary for RoBorregos/Home-Docs. This period focused on delivering core feature capabilities in vision and HRI knowledge management, with an emphasis on business value such as improved autonomous perception and faster knowledge access. Key deliveries include Moondream-based pose detection and beverage location identification in the vision system, and a Retrieval-Augmented Generation (RAG) based Q&A system across three knowledge bases (frida, roborregos, tec de monterrey) with a quiz vs context scoring mechanism. No major bugs were escalated this month; the work was feature-driven and centered on system integration. The contributions demonstrate cross-functional collaboration, robust version-control discipline, and progress toward more autonomous and informed human-robot interaction, with spotlight updates reflecting Jocelyn's active participation.

February 2025 — Multi-repo delivery across RoBorregos/home2 and RoBorregos/Home-Docs focusing on wake word robustness, flexible model management, enhanced downstream processing, and documentation clarity. Implementations include wake word cooldown, dynamic loading of ONNX models, dependency upgrades for latest wake word capabilities, enhanced wake word publication (keyword + score), addition of no-detection models, and updated Spotlights documentation reflecting image analysis methods and task progress.

January 2025: Delivered three high-impact features across two repos to advance HRI performance evaluation, image understanding, and wake word readiness. Key outcomes include (1) KWS models documentation and synthetic audio data for performance metrics, (2) Moondream image analysis utility with a class-based MoondreamWrapper and usage examples, and (3) a ROS OpenWakeWord node with lint improvements and updated model loading. Implemented quality improvements via lint fixes and a robust default model path to reduce runtime issues. Engaged in GitHub discussions to refine KWS metrics. Business value: improved evaluation capabilities, streamlined tooling, and more reliable wake word detection.