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Article Dans Une Revue IEEE Robotics and Automation Letters Année : 2022

Motor-level N-MPC for Cooperative Active Perception with Multiple Heterogeneous UAVs

Résumé

This paper introduces a cooperative control framework based on Nonlinear Model Predictive Control (NMPC) for solving an Active Information Acquisition problem (AIA) using a system of multiple multirotor UAVs equipped with onboard sensors. The observation task of the NMPC is a minimumuncertainty pose estimation of a moving feature which is observed by the multi-UAV system, using a cooperative Kalman filter. The controller considers a full nonlinear model of the multirotors-including the motor-level actuation units and their real constraints in terms of maximum torque-and embeds the Kalman filter estimation uncertainty in its prediction. The framework allows and exploits heterogeneity in the actuation and sensing systems by considering a generic model of UAVincluding both quadrotors and tilted-propeller multirotors-and a generic model of range-and-bearing sensor with arbitrary rate and field of view. The capability of the proposed framework to reduce the cooperative estimation uncertainty of a static or a moving feature, thus leading the system to optimal sensing configurations, is demonstrated through Gazebo simulations and real experiments. The software is provided open-source.
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Dates et versions

hal-03482081 , version 1 (15-12-2021)
hal-03482081 , version 2 (27-01-2022)
hal-03482081 , version 3 (24-03-2022)

Identifiants

Citer

Martin Jacquet, Max Kivits, Hemjyoti Das, Antonio Franchi. Motor-level N-MPC for Cooperative Active Perception with Multiple Heterogeneous UAVs. IEEE Robotics and Automation Letters, 2022, 7 (2), pp.2063 - 2070. ⟨10.1109/LRA.2022.3143218⟩. ⟨hal-03482081v3⟩
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