NMPC strategy for a quadrotor UAV in a 3D unknown environment
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Universidade Federal de Minas Gerais
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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.
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Aeronave não tripulada
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Unmanned Aerial Vehicles , Nonlinear Model Predictive Control , Control Strategy , Numerical Results , Energy State , Model Predictive Control , Obstacle Avoidance , Sensor Information , Model Predictive Control Strategy , Static Obstacles , Optimization Problem , Cost Function , Optimal Control , Polyhedral , Nonlinear Programming , Edge Weights , Terminal Region , Path Planning , Linear Constraints , Safe Region , Optimal Control Problem , Rapidly-exploring Random Tree , Nonlinear Programming Problem , Solution Of The Optimal Control Problem , Convex Polytope , Terminal Constraint , Range Of Sensors , Model Predictive Control Framework , 2D Environment
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https://ieeexplore.ieee.org/document/8981556