Software-ontwikkelaar
Pubblicato il 07-08-2026 - TXT GROUP in Italia
TXT e-Tech , a company of the TXT Group, is looking for a candidate for a Master’s thesis focused on the research, design, implementation and validation of swarming, formation and multi-agent coordination algorithms within a proprietary product.
The project is part of TXT’s modular cloud-based platform for the simulation of unmanned systems ( UAV, UGV, USV, eVTOL ), which integrates the entire UxV operational lifecycle: mission design, planning, real-time simulation (C++ core), and KPI-based debriefing within a single environment.
The candidate will contribute to the evolution of the Autonomy & Guidance Layer and the Swarming & Teaming Behaviour Engine (currently TRL 3) , working on:
Formation control (leader–follower, virtual structure)
Decentralized swarming based on swarm intelligence
Cooperative task allocation for heterogeneous fleets
Main responsibilities:
Literature review on state-of-the-art formation, swarming and coordination algorithms for UxV systems
Algorithm design and formalisation with attention to computational efficiency and real-time constraints
Implementation of selected algorithms as software modules compatible with a C++ simulation core and microservices architecture
Simulation-based validation within a structured environment (scenario design, test campaigns, KPI evaluation)
Documentation and thesis write-up including analysis of results, limitations and future development directions
Required technical skills:
Fundamentals of control theory and/or multi-agent systems
Programming in C++
Programming in Python
Familiarity with simulation environments (e.g. Gazebo, MATLAB/Simulink)
Understanding of swarm intelligence or formation control principles
Nice to have:
Experience with multi-robot coordination or distributed algorithms
Multi-agent reinforcement learning
Knowledge of MAVLink, ROS/ROS2 or drone communication protocols
Familiarity with HLA/DIS standards for distributed simulation
Optimisation techniques (genetic algorithms, metaheuristics, gr