Vision-based particle filtering for quad-copter attitude estimation using multirate delayed measurements - Sadeghzadeh-Nokhodberiz, Nargess; Iranshahi, Mohammad; Montazeri, Allahyar (Frontiers in Robotics and AI, 2023)
In this paper, the problem of attitude estimation of a quad-copter system equipped with multi4 rate camera and gyroscope sensors is addressed through extension of sampling importance re-sampling (SIR) particle filter (PF). Attitude measurement sensors, such as cameras, usually suffer from slow sampling rate and processing time delay compared to inertial sensors, such as gyroscopes. A discretized attitude kinematics in Euler angles is employed where the gyroscope noisy measurements are considered as the model input leading to a stochastic uncertain system model. Then, a multirate delayed PF is proposed so that when no camera measurement is available, the sampling part is performed only. In this case, the delayed camera measurements are used for the weight computation and re-sampling. Finally, the efficiency of the proposed method is demonstrated through both numerical simulation and experimental work on Dji Tello quad-copter system. The images captured by the camera are processed using ORB feature extraction method and the Homography method in Python-OpenCV is used to calculate the rotation matrix from the Tello’s image frames.