Week 9 Progress

Eric – Spent time refining the robot's base navigation to improve reliability and responsiveness. Also drafted the initial version of our final presentation video script, outlining key visuals and narration to tell the story of our project.

Iman – Successfully identified the ArUco marker using the new setup frame, helping to improve alignment accuracy for sensor placement. Also provided feedback on the video flow.

Sohrab – Rescanned the environment map to ensure better localization and smoother navigation. Worked on adjusting pose movements and further tuning the base navigation to handle different room layouts.

Script

Every 5 minutes a nurse somewhere stops to check a patient’s blood sugar. For elderly or immobile patients, that quick check means another hallway sprint and another break in care elsewhere. Nurses call the workload unsustainable.

Traditional finger‑sticks give only snapshots, and even continuous glucose monitors only help if someone can place them on the patient’s arm—something many seniors simply can’t do alone.

What if the sensor came to the patient—autonomously, safely, anytime day or night?

Meet our autonomous glucometer‑delivery system. Built on the Hello Robot Stretch 2, it navigates hospital rooms, aligns with a padded positioning frame, and applies a Libre sensor—all at the push of a button.

Lindsay, a diabetes research nurse with extensive experience in elderly patient care, emphasized how important it is for the robot to adapt to patients with limited mobility.

An, an 82‑year‑old diabetic patient with limited dexterity and vision impairments, shared, “This seems very helpful. I think it would really make a difference for me and my daughter, who helps take care of me most of the time. It could take some of the pressure off her and make things a bit easier for both of us.”

Introduce Stretch Four Sugar

…

We’re Sohrab, Eric, and Iman—three Computer Science students at the University of Washington. Sohrab focused on saved poses and robot movements. Eric worked on the navigation system and user interface. Iman worked on detecting ArUco markers and aligning the robot with the patient’s arm for accurate sensor placement.

Thank you for listening