The improvement of efficiency in the control and planning of multi-agent systems and the subsequent experimental validation of these advances is the “leitmotif” of the project. Taking into account the growing demand for multi-agent control applications in fields as diverse as precision agriculture, surveillance, rescue, etc., it is expected that the knowledge acquired during the execution of the project has scientific-technical impact in terms of publications in relevant forums, tutorials and software developed by the team.

In this project, new control and planning strategies will be developed and experimentally validated with application to multi-agent systems.

The project is the result of the coordination of two sub-projects: the first will focus on improving the functional efficiency of such control algorithms, e.g. greater robustness in the face of variable uncertainties in time/delay mismatches, and the second will integrate advances in the optimal planning and control of a mobile robot team with limited resources.

It is expected to advance in the knowledge on theoretical aspects of control and planning systems under delays, uncertainty and heterogeneous agents and their experimental validation.

The ai2 Institute coordinates the first subproject that is dedicated to exploring new control and planning strategies in multi-agent systems based on the current limitations reported in the literature: robustness in the face of model uncertainty, time-varying delay mismatches, input saturation constraints and bandwidth/power constraints. Despite previous contributions on this topic, there is much room for improvement in the sense of improving efficiency and functional performance.

Therefore, the objective is twofold:

• advance knowledge on the theoretical aspects of control and planning systems under delays, uncertainty and heterogeneous agents,
• To construct an experimental configuration to validate the effectiveness of the control strategies designed.