Experimental Validation of Sensitivity-Aware Trajectory Planning for a Quadrotor UAV Under Parametric Uncertainty

Srour, Ali; Marcellini, Salvatore; Belvedere, Tommaso; Cognetti, Marco; Franchi, Antonio; Giordano, Paolo Robuffo

doi:10.1109/icuas60882.2024.10556958

2024 International Conference on Unmanned Aircraft Systems (ICUAS) 2024

DOI: 10.1109/icuas60882.2024.10556958

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Experimental Validation of Sensitivity-Aware Trajectory Planning for a Quadrotor UAV Under Parametric Uncertainty

Ali Srour,

Salvatore Marcellini,

Tommaso Belvedere

et al.

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Safe and Robust Planning for Uncertain Robots: A Closed-Loop State Sensitivity Approach

Afifi,

Belvedere,

Pupa

et al. 2024

IEEE Robot. Autom. Lett.

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In this work, we detail a comprehensive framework for safe and robust planning for robots in presence of model uncertainties. Our framework is based on the recent notion of closed-loop state sensitivity, which is extended in this work to also include uncertainties in the initial state. The proposed framework, which considers the sensitivity of the nominal closedloop system w.r.t. both model parameters and initial state mismatches, is exploited to compute tubes that accurately capture the worst-case effects of the considered uncertainties. In comparison to the current state-of-the-art for safe and robust planning, the proposed closed-loop state sensitivity framework has the important advantage of computational simplicity and minimal assumptions (and simplifications) regarding the underlying robot closed-loop dynamics. The approach is validated via both extensive simulations and real-world experiments. In the experiments we consider as case study a nonlinear trajectory optimization problem aimed at generating an intrinsically robust and safe trajectory for an aerial robot for safely performing an obstacle avoidance maneuver despite the uncertainties. Simulation and experimental results further confirm the viability and interest of the proposed approach.

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Safe and Robust Planning for Uncertain Robots: A Closed-Loop State Sensitivity Approach

Afifi,

Belvedere,

Pupa

et al. 2024

IEEE Robot. Autom. Lett.

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show abstract

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Experimental Validation of Sensitivity-Aware Trajectory Planning for a Quadrotor UAV Under Parametric Uncertainty

Cited by 1 publication

References 22 publications

Safe and Robust Planning for Uncertain Robots: A Closed-Loop State Sensitivity Approach

Safe and Robust Planning for Uncertain Robots: A Closed-Loop State Sensitivity Approach

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