Visual Servoing for an Autonomous Hexarotor Using a Neural Network Based PID Controller
AbstractIn recent years, unmanned aerial vehicles (UAVs) have gained significant attention. However, we face two major drawbacks when working with UAVs: high nonlinearities and unknown position in 3D space since it is not provided with on-board sensors that can measure its position with respect to a global coordinate system. In this paper, we present a real-time implementation of a servo control, integrating vision sensors, with a neural proportional integral derivative (PID), in order to develop an hexarotor image based visual servo control (IBVS) that knows the position of the robot by using a velocity vector as a reference to control the hexarotor position. This integration requires a tight coordination between control algorithms, models of the system to be controlled, sensors, hardware and software platforms and well-defined interfaces, to allow the real-time implementation, as well as the design of different processing stages with their respective communication architecture. All of these issues and others provoke the idea that real-time implementations can be considered as a difficult task. For the purpose of showing the effectiveness of the sensor integration and control algorithm to address these issues on a high nonlinear system with noisy sensors as cameras, experiments were performed on the Asctec Firefly on-board computer, including both simulation and experimenta results. View Full-Text
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Lopez-Franco, C.; Gomez-Avila, J.; Alanis, A.Y.; Arana-Daniel, N.; Villaseñor, C. Visual Servoing for an Autonomous Hexarotor Using a Neural Network Based PID Controller. Sensors 2017, 17, 1865.
Lopez-Franco C, Gomez-Avila J, Alanis AY, Arana-Daniel N, Villaseñor C. Visual Servoing for an Autonomous Hexarotor Using a Neural Network Based PID Controller. Sensors. 2017; 17(8):1865.Chicago/Turabian Style
Lopez-Franco, Carlos; Gomez-Avila, Javier; Alanis, Alma Y.; Arana-Daniel, Nancy; Villaseñor, Carlos. 2017. "Visual Servoing for an Autonomous Hexarotor Using a Neural Network Based PID Controller." Sensors 17, no. 8: 1865.
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