This week, I focused primarily on project planning, requirement analysis, and initial hardware preparation. At the beginning of the week, I worked with my teammate to prepare and refine our project proposal, helping to define the technical goals, system architecture, and evaluation metrics. After the proposal presentation, I continued collaborating to clarify design details, especially those related to usability and safety for elderly users.
I then analyzed the use-case requirements in more depth and translated them into concrete technical parameters. In particular, I evaluated what following speed, camera field of view, frame rate, and computational capability would be necessary to reliably track a person indoors. Based on these requirements, I compared available hardware options and helped determine that a Raspberry Pi 5, a USB camera with sufficient resolution and field of view, and a UGV robot base would meet our needs. I reviewed the specifications of these components to ensure they could support real-time YOLO inference and safe obstacle avoidance.
Finally, I worked with my teammate to finalize the list of required materials and submit equipment requests. We are currently slightly behind the original hardware setup schedule, mainly due to the time needed to research appropriate components and the ordering process. However, given the long overall project timeline and the fact that this delay is largely logistical rather than technical, the setup delay is acceptable and should not affect major milestones. For next week, I plan to begin software setup on the Raspberry Pi, start building the vision pipeline, and assist with initial hardware integration once the components arrive.
