Altan, Aytaç | Bayraktar, Köksal | Hacıoğlu, Rıfat

Proceedings | 2016 | 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings , pp.1433 - 1436

In this stuidy, the position information from ultrasound sensors on UAV related to floor gallery mine passed through the filter, it is aimed to control the position of simultaneously creating the optimum environmental map. The simultaneous in galleries made mapping, mine the data of air to the designated central monitoring system with real-time location information is transmitted to the ventilation system, which is intended to more effectively work in the mines. The gallery maps which simultaneous location and mapping information obtained by UAV Extended Kalman Filter algorithms processed were obtained experimentally. © 2016 IEEE.

Karasu, Seçkin | Altan, Aytaç | Saraç, Zehra | Hacıoğlu, Rıfat

Proceedings | 2017 | 2017 25th Signal Processing and Communications Applications Conference, SIU 2017 , pp.1433 - 1436

In this study, the wind speed prediction model is created that gives a minimum error for different hidden layer neuron numbers and delay step numbers. Using the one-minute time series, the prediction of the next wind speed is performed with the NAR neural network model. The predicted values of wind speed obtained are compared with predicted values of wind speed obtained with filter methods. For different window functions and lengths, wind speed prediction is made using filters with different weight coefficients. For the number of hidden layer neurons is 14 and the number of delay steps is 10, MAE, MSE and RMSE values are calculated . . .as 0.0315, 0.0019, 0.0445, respectively, with NAR neural network. It is seen that the proposed method for the wind speed dataset has a higher prediction performance than thefilter methods. © 2017 IEEE Daha fazlası Daha az

Kulu, Nükhet | Başkaya, Merve | Keleş, Aysel | Altan, Aytaç | Hacıoğlu, Rıfat

Proceedings | 2018 | 2018 2ND INTERNATIONAL SYMPOSIUM ON MULTIDISCIPLINARY STUDIES AND INNOVATIVE TECHNOLOGIES (ISMSIT) , pp.290 - 293

In this study, it is aimed to determine the number of reference fruits and health status (sturdy, rotten, mottled, non-spotted) by using real-time image or recorded video taken from the autonomous Unmanned Aerial Vehicle (UAV) camera in orchards. In the determinations made by using image processing techniques, sturdy-rotten and mottled-speckless distinction are made for oranges and apricots, respectively. These distinction and determination processes are carried out using highly trained classifiers. Three types of multi-trained classifiers performance have been compared and a highly trained classifier which has high performance has . . .been preferred for object detection. The accuracy of the Haar, local binary pattern (LBP), and histogram of oriented gradients (HOG) classifiers are compared in Python using the open source computer vision library. It has been shown experimentally that Haar classifier achieves high performance in determining real-time reference fruit health status and yield. Daha fazlası Daha az

Altan, Aytaç | Hacıoğlu, Rıfat

Proceedings | 2014 | 2014 22ND SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) , pp.1686 - 1689

In this study, unmanned vehicles used for target tracking camera RRP (revolute revolute prismatic) joint structure with a three-jointed robot arm with the position, velocity and acceleration control is made. In order to be able to follow the specified trajectory, the system used in the control of the robot arm with joint structure RRP target tracking model based on changing according to the structure proposed by the MPC is implemented. Also the PID (Proportional Integral Dervative) is provided with control comparison was made. MATLAB/Simulink simulations performed unmanned vehicles used for target tracking in robotic camera control . . .with the system were investigated in the MPC Daha fazlası Daha az

Altan, Aytaç | Hacıoğlu, Rıfat

Conference Object | 2017 | 2017 25th Signal Processing and Communications Applications Conference, SIU 2017 , pp.1686 - 1689

This study focuses on the modelling of 3 axis gimbal system with the RRR joint structure on the Unmanned Aerial Vehicle (UAV), which is autonomously moving for the target tracking, based on experimental input (motor velocities) and output (end effector position) data. The fact that UAVs move in a certain direction and that the camera on the end effector of the gimbal system on it is adhere to the correct target attracts many researchers. The transfer function of the 3 axis gimbal system is obtained by linearly structured OE-Output Error model using experimentally obtained data under different external disturbance effects. Model degr . . .ee is determined and data set based verification is applied. Also, the performance is compared by examining the effect of external disturbance in the transfer function obtained. © 2017 IEEE Daha fazlası Daha az