Alejandro Botas Bárcena defends his Telematics BSc thesis on distributed mission planning for UAVs

Created in April 15, 2026 by Néstor Lucas Martínez

2026   ·   bachelor-thesis   mission-planning   uav   precision-agriculture   cloud-computing   path-planning   A-star   AFarCloud   ·   news

🎓 Bachelor’s Thesis Defense with Excellent Grade

On Tuesday, April 15, 2026, my student Alejandro Botas Bárcena successfully defended his Bachelor’s Thesis titled “Distributed mission planning system for unmanned autonomous vehicles”. The evaluation committee awarded him a grade of 9.5 out of 10 (Excellent).

This thesis tackles the challenge of intelligent, cloud‑based mission planning for unmanned aerial vehicles (UAVs) in precision agriculture. Building on the European AFarCloud initiative, Alejandro designed and implemented a distributed system that separates user interaction (lightweight web client) from computationally intensive tasks (cloud server). The result is a scalable, modular platform that generates optimised flight plans for agricultural drones.

Key technical contributions

  • Distributed architecture with a Python/Flask server (REST API) and a JavaScript web client, enabling remote mission configuration, planning, and visualisation.
  • Two integrated path‑planning algorithms:
    • Closest Neighbour – fast, scalable heuristic for large waypoint sets.
    • A* – optimal route generation using a cost‑based search with Euclidean heuristics.
  • Flexible mission definition – users can set grid size, mission type (inspection, treatment, or both), and algorithm preference. The system produces structured JSON missions compatible with the AFarCloud information model.
  • Rigorous validation following IEEE 29119 standards, including functional tests (client‑server communication, JSON schema compliance, algorithm consistency) and non‑functional performance tests. The results clearly show the trade‑off: A* gives shorter paths but becomes slower with >20 waypoints, while Closest Neighbour remains extremely fast even with >70 waypoints.

Impact and alignment

Alejandro’s work is directly relevant to real‑world precision agriculture. The system has been integrated into the OpenTech Lab of the GRyS research group. It supports sustainable farming by optimising drone routes, reducing flight time, energy use, and chemical application. The project also aligns with several UN Sustainable Development Goals (SDG 2 – Zero Hunger, SDG 9 – Industry and Innovation, SDG 12 – Responsible Consumption and Production).

The thesis includes a complete budget analysis (€13,421.18 total estimated cost) and identifies clear future improvements: optimising A* for large missions, adding forbidden‑area constraints, integrating fleet coordination, and extending the client to mobile devices.

Alejandro’s work demonstrates excellent analytical and implementation skills, bridging cloud computing, robotics, and agricultural automation. I congratulate him on this well‑deserved success and look forward to seeing his contributions to the NexTArc project and beyond.