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Embedded Fast Nonlinear Model Predictive Control for Micro Aerial Vehicles


Very small size or micro, aerial vehicles are being recently studied due to the large influence of environmental disturbances. The multirotor aerial vehicle (MAV) usually requires control approaches that can guarantee a safe operation. However, limitations with respect to the embedded system (i.e. energy, processing power, memory, etc.) are usually present. In this work, we propose the use of Nonlinear model predictive control (NMPC), which can safely respect input constraints. In contrast, the application of NMPC in embedded systems of Micro-MAV is typically challenging. To solve this issue, we propose a modification on the NMPC called Embedded Fast NMPC that can ensure the implementation of the position controller safely and stably. Micro Multirotor Aerial Vehicles (Micro-MAVs) use low processing power boards. These boards usually rely solely on on-board sensors to perform localization and target detection, which in turn makes this platform suitable for experiments in GNSS-denied environments. We validate our approach with real robot experiments using a Micro-MAV.

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The presented work has been supported by the Czech Science Foundation (GAČR) under research project No. 20-10280S, by the EU AERIAL CORE 2020-2023 project under the H2020 ICT-10-2019-2020: Robotics Core Technology call, and by the Ministry of Education of the Czech Republic has also funded this research by OP VVV funded project CZ.02.1.01/0.0/0.0/16 019/0000765 ”Research Center for Informatics”.

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Correspondence to Tiago Nascimento.

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Nascimento, T., Saska, M. Embedded Fast Nonlinear Model Predictive Control for Micro Aerial Vehicles. J Intell Robot Syst 103, 74 (2021).

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  • Fast NMPC
  • Micro multirotor aerial vehicles
  • Position control