This work presents a Nonlinear Model Predictive Control strategy for a quadrotor UAV with obstacle avoidance capability in a 3D unknown environment with static obstacles. The system aims to reach the target in minimum time while avoiding obstacles and also to take into account the energy of states and inputs. Sensor information is processed to detect the obstacles and obtain the inequality constraints of an obstacle-free zone. Numerical results are presented to attest the performance of the system.
(2019). NMPC Strategy for a Quadrotor UAV in a 3D Unknown Environment . Retrieved from http://hdl.handle.net/10446/169404
NMPC Strategy for a Quadrotor UAV in a 3D Unknown Environment
Ferramosca, Antonio;
2019-01-01
Abstract
This work presents a Nonlinear Model Predictive Control strategy for a quadrotor UAV with obstacle avoidance capability in a 3D unknown environment with static obstacles. The system aims to reach the target in minimum time while avoiding obstacles and also to take into account the energy of states and inputs. Sensor information is processed to detect the obstacles and obtain the inequality constraints of an obstacle-free zone. Numerical results are presented to attest the performance of the system.| File | Dimensione del file | Formato | |
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ICAR19_0226_FI.pdf
Open Access dal 07/02/2022
Descrizione: This is a post-peer-review, pre-copyedit version of an article published in 2019 19th International Conference on Advanced Robotics (ICAR), Electronic ISBN:978-1-7281-2467-4. The final authenticated version is available online at: http://dx.doi.org/10.1109/ICAR46387.2019.8981556
Versione:
postprint - versione referata/accettata senza referaggio
Licenza:
Licenza default Aisberg
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1.53 MB
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Adobe PDF
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