Perception-constrained and Motor-level Nonlinear MPC for\propeller UAVs

M. Jacquet, G. Corsini, D. Bicego, A. Franchi

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

1 Citation (Scopus)


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.
Original languageEnglish
Title of host publication2020 IEEE International Conference on Robotics and Automation (ICRA
Place of PublicationParis, France
Number of pages1
Publication statusPublished - 1 May 2020
EventInternational Conference on Robotics and Automation, ICRA 2020 - Virtual Conference, Paris, France
Duration: 31 May 202031 Aug 2020


ConferenceInternational Conference on Robotics and Automation, ICRA 2020
Abbreviated titleICRA 2020
Internet address


  • murophen
  • aerialcore
  • flyingcoworker

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