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

Abstract : 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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https://hal.laas.fr/hal-03482081
Contributor : Martin Jacquet Connect in order to contact the contributor
Submitted on : Wednesday, December 15, 2021 - 4:43:33 PM
Last modification on : Tuesday, April 5, 2022 - 3:40:39 AM
Long-term archiving on: : Wednesday, March 16, 2022 - 7:29:35 PM

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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, IEEE In press, 7 (2), pp.2063 - 2070. ⟨10.1109/LRA.2022.3143218⟩. ⟨hal-03482081v1⟩

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