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Perception-constrained and Motor-level Nonlinear MPC for both Underactuated and Tilted-propeller UAVS

Abstract : In this paper, we present a Perception-constrained Nonlinear Model Predictive Control (NMPC) framework for the real-time control of multi-rotor aerial vehicles. Our formulation considers both constraints from a perceptive sensor and realistic actuator limitations that are the rotor minimum and maximum speeds and accelerations. The formulation is meant to be generic and considers a large range of multi-rotor platforms (such as underactuated quadrotors or tilted-propellers hexarotors) since it does not rely on differential flatness for the dynamical equations, and a broad range of sensors, such as cameras, lidars, etc... The perceptive constraints are expressed to maintain visibility of a feature point in the sensor's field of view, while performing a reference maneuver. We demonstrate both in simulation and real experiments that our framework is able to exploit the full capabilities of the multi-rotor, to achieve the motion under the aforementioned constraints, and control in real-time the platform at a motor-torque level, avoiding the use of an intermediate unconstrained trajectory tracker.
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https://hal.laas.fr/hal-02974320
Contributor : Martin Jacquet <>
Submitted on : Wednesday, October 21, 2020 - 5:14:37 PM
Last modification on : Thursday, June 10, 2021 - 3:06:41 AM

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Martin Jacquet, Gianluca Corsini, Davide Bicego, Antonio Franchi. Perception-constrained and Motor-level Nonlinear MPC for both Underactuated and Tilted-propeller UAVS. IEEE International Conference on Robotics and Automation (ICRA 2020), May 2020, Paris (Virtual Conference), France. pp.4301-4306, ⟨10.1109/ICRA40945.2020.9197281⟩. ⟨hal-02974320⟩

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