Title :

Visual soft landing of an autonomous quadrotor on a moving pad using a combined fuzzy velocity control with model predictive control

Author(s) :

Bouaiss, Oussama [Auteur]
Mechgoug, Raihane [Auteur]
Taleb-Ahmed, Abdelmalik [Auteur]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
COMmunications NUMériques - IEMN [COMNUM - IEMN]

Journal title :

Signal, Image and Video Processing

Pages :

21–30

Publisher :

Springer Verlag

Publication date :

2023-02

ISSN :

1863-1703

English keyword(s) :

Unmanned aerial vehicles
Quadrotor
Video processing
landing
Fuzzy logic
Model predictive Control
Pose estimation

HAL domain(s) :

Sciences de l'ingénieur [physics]

English abstract : [en]

Autonomous landing is a vital option for Unmanned Aerial vehicles (UAV), as it can be a fail-safe in many critical cases. This paper demonstrates a complete solution for the soft landing application of a fully autonomous ...
Show more >Autonomous landing is a vital option for Unmanned Aerial vehicles (UAV), as it can be a fail-safe in many critical cases. This paper demonstrates a complete solution for the soft landing application of a fully autonomous quadrotor on a moving pad considering external disturbance, model uncertainties, and actuators noise. The challenge starts with detecting the specially designed landing pad by an onboard vision system, a robust Algorithm estimates its coordinates precisely using a camera pose estimation. An enhanced Kalman filter by Madgwick data fusion of asynchronous sensors was developed for the best relative pose and heading reference. Different sizes and designs of the ArUco markers were attentively chosen to ensure the best detection at different altitudes and angles of approach. The landing trajectory is dynamically generated based on Jerk optimization, integrating a bio-inspired velocity profile by Fuzzy Logic Controller (FLC) to smoothen the landing. Model Predictive Control (MPC) was opted for quadrotor control to track the generated trajectory in time reference with the rejection of disturbance. The solution presents a soft mechanism for flat surface landing similar to human decision concept and control. The proposed method ensures absorption of the shock of impact, and the optimal tracking of the moving landing pad at less than 4 cm of error in Cartesian coordinates. Experimental results from pad relative pose estimation developed in Python, Data fusion experimentation of Attitude and Heading Reference system (AHRS), and Matlab simulations with a performance comparison between MPC and Proportional Integral Derivative (PID) control validate the effectiveness and reliability of the proposed landing task solution.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Institut d'Électronique, de Microélectronique et de Nanotechnologie (IEMN) - UMR 8520

Source :

Harvested from HAL