Luigi Iannelli

Giuseppe Silano, Quentin Sablé, Marco Tognon et al.

This paper presents a sensitivity-based tube Nonlinear Model Predictive Control (NMPC) framework for cooperative aerial chains under bounded parametric uncertainty. We consider a planar two-vehicle chain connected by rigid links, modeled with input-rate actuation to enforce slew-rate and magnitude limits on thrust and torque. Robustness to uncertainty in link mass, length, and inertia is achieved by propagating first-order parametric state sensitivities along the horizon and using them to compute online constraint-tightening margins. We robustify an inter-link separation constraint, implemented via a smooth cosine embedding, and thrust-magnitude bounds. The method is implemented in MATLAB and evaluated with boundary-hugging maneuvers and Monte-Carlo uncertainty sampling. Results show improved constraint margins under uncertainty with tracking performance comparable to nominal NMPC.

Giuseppe Silano, Davide Liuzza, Luigi Iannelli et al.

Inspection of power line infrastructures must be periodically conducted by electric companies in order to ensure reliable electric power distribution. Research efforts are focused on automating the power line inspection process by looking for strategies that satisfy different requirements expressed in terms of potential damage and faults detection. This problem comes up with the need of safe planning and control techniques for autonomous robots to perform visual inspection tasks. Such an application becomes even more interesting and of critical importance when considering a multi-robot extension. In this paper, we propose to compute feasible and constrained trajectories for a fleet of quad-rotors leveraging on Signal Temporal Logic (STL) specifications. The planner allows to formulate rather complex missions avoiding obstacles and forbidden areas along the path. Simulations results achieved in MATLAB show the effectiveness of the proposed approach leading the way to experimental tests on the hardware.