What was accomplished

●       The software team set up the core development environment on the Raspberry Pi 4, installing Python, OpenCV, and the YOLOv11 framework in preparation for onboard target detection.

●       A MAVProxy link was established between the two ground-station laptops over a local LAN, allowing MAVLink telemetry data to be shared and mirrored across both machines in real time.

●       Version control and a shared code repository were set up so both hardware and software sub-teams could track changes to configuration files and scripts consistently.

Challenges and solutions

The main challenge was configuring MAVProxy to correctly forward the MAVLink stream between two separate laptops without packet loss or conflicting output ports. This was resolved by assigning distinct UDP output ports for each laptop and verifying the link with a continuous ping and heartbeat test before moving forward.

Next steps plan

Begin researching and evaluating mapping algorithm approaches for generating a georeferenced map of the search area.