Midterm Feedback and Algorithm Development

The midterm presentation didn’t go as smoothly as we had hoped. While our technical content was solid, we realized that our delivery lacked clarity and fluidity in key moments. The presentation’s impact was hindered by the complexity of our explanations and the way we presented the system’s architecture.

Taking this feedback seriously, we returned to the algorithm development phase with a renewed focus. We continued building our custom protocol, HMAV-LoRa, which integrates MAVLink communication, RSSI-based dynamic routing, and reactive fallback mechanisms inspired by AODV.

In this model, the mother drone acts as a central node when possible, while each servo drone can switch parents based on RSSI strength in case of failure or signal degradation. Additionally, the system can fall back on limited flooding to re-establish routes when other strategies fail.

We also tried implementing lightweight message serialization for telemetry, optimizing payload size for LoRa transmission. These technical adjustments are helping us move closer to a robust, real-world-ready system.