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All Journal IAES International Journal of Robotics and Automation (IJRA)
Ali Jebelli
University of Alberta
Automotive Engineering Electrical & Electronics Engineering

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Efficient commercial classification of agricultural products using convolutional neural networks Ali Jebelli; Arezoo Mahabadi; Rafiq Ahmad
IAES International Journal of Robotics and Automation (IJRA) Vol 10, No 4: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v10i4.pp353-364

Abstract

Agricultural products, as essential commodities, are among the most sought - for items in superstores. Barcode is usually utilized to classify and regulate the price of products such as ornamental flowers in such stores. However, the use of barcodes on some fragile agricultural products such as ornamental flowers can be damaged and lessen their life length. Moreover, it is time - consuming and costly and may lead to the pro duction of massive waste and damage to the environment and the admittance of chemical materials into food products that can affect human health. Consequently, we aimed to design a classifier robot to recognize ornamental flowers based on the related produc t image at different times and surrounding conditions. Besides, it can increase the speed and accuracy of distinguishing and classifying the products, lower the pricing time, and increase the lifetime due to the absence of the need for movement and changin g the position of the products. According to the datasheets provided by the robot that is stored in its database, we provide the possibility of identifying and introducing the product in different colors and shapes. Also, due to the preparation of a standa rd and small database tailored to the needs of the robot, the robot will be trained in a short time (less than five minutes) without the need for an Internet connection or a large hard drive for storage the data. On the other hand, by dividing each input p hoto into ten different sections, the system can, without the need for a detection system, simultaneously in several different images, decorative flowers in different conditions, angles and environments, even with other objects such as vases, detects very fast with a high accuracy of 97%.
Fault tolerance of a quadrotor via feedback linearization approach Ali Jebelli; Alireza Najafiyanfar; Arezoo Mahabadi; Mustapha C. E. Yagoub
IAES International Journal of Robotics and Automation (IJRA) Vol 12, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v12i3.pp228-239

Abstract

A control algorithm is proposed to efficiently control the state, position, and height of a nonlinear dynamic model of a quadcopter. Based on feedback linearization, a state space model is presented for the system with the controller with a two-loop control structure designed and implemented in it. The inner and faster controller is responsible for adjusting the quadcopter height and angles, and the outer and slower controller is responsible for changing the desired figures of roll and pitch angles to control the system position. Whenever a rotor of the quadcopter rotor fails, the status and position of the system are converged and the system is stabilized. Simulation results based on different scenarios indicate the proper performance of the control system whenever there are external disturbances. Note that the gyroscopic effects because of the propeller rotation were not considered.
Designing and implementing a multi-function board to increase the operation time of mobile robots using solar panels Ali Jebelli; Arezoo Mahabadi
IAES International Journal of Robotics and Automation (IJRA) Vol 12, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v12i3.pp248-261

Abstract

Today, the use of mobile robots and autonomous vehicles has increased due to their use in various industries, and their performance and duration of operation largely depend on the amount of energy consumed and their batteries. One of the ways to increase the operation time of robots is the use of solar panels that can charge their batteries while moving, but the amount of energy received from solar panels reduces their efficiency due to factors affecting them, such as the angle of the sun, weather conditions, and their use in mobile robots alone is not recommended. In this research, we introduce an electric circuit with very low losses to increase the received power of solar panels and increase their efficiency, which is able to supply the power of the robot through solar panels when the sunlight and the angle of radiation are suitable and charge the batteries through the maximum power point controller (MPPC), and by reducing the amount of energy received from the panels by changing the energy source to the battery, the duration of the system’s dependence on the battery has decreased, which increases the duration of the mobile robots.
Co-Authors Alireza Najafiyanfar Arezoo Mahabadi Mustapha C. E. Yagoub Rafiq Ahmad