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Journal : International Journal of Robotics and Control Systems

Implementation of DC Motor PID Control On Conveyor for Separating Potato Seeds by Weight Daniya Sonny Febriyan; Riky Dwi Puriyanto
International Journal of Robotics and Control Systems Vol 1, No 1 (2021)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v1i1.221

Abstract

Dieng area is a mountainous area, dieng has land with high fertility levels so that they are increasingly high in the agricultural sector, especially potatoes. During the time, the technology for sorting potato seeds was still manual with humans, so it was less effective. The conveyor here is very useful as this device which will later work with loadcell as a weigher, and this device will be driven using a dc motor then the speed stabilization uses the PID algorithm with trial and error methods and this tool is supported using ultrasonic sensors and two servo sorting. This device works with 1 cycle, namely with 1 command with a value of KP 55, KI 20 and KD 0.001. The conveyor movement is quite stable with an average error value of 0.276 load cell with a standard deviation of 0.211877 with an achievement level of 80%.
Artificial Potential Field Path Planning Algorithm in Differential Drive Mobile Robot Platform for Dynamic Environment Maulana Muhammad Jogo Samodro; Riky Dwi Puriyanto; Wahyu Caesarendra
International Journal of Robotics and Control Systems Vol 3, No 2 (2023)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v3i2.944

Abstract

Mobile robots need path-planning abilities to achieve a collision-free trajectory. Obstacles between the robot and the goal position must be passed without crashing into them. The Artificial Potential Field (APF) algorithm is a method for robot path planning that is usually used to control the robot for avoiding obstacles in front of the robot. The APF algorithm consists of an attractive potential field and a repulsive potential field. The attractive potential fields work based on the predetermined goals that are generated to attract the robot to achieve the goal position. Apart from it, the obstacle generates a repulsive potential field to push the robot away from the obstacle. The robot's localization in producing the robot's position is generated by the differential drive kinematic equations of the mobile robot based on encoder and gyroscope data. In addition, the mapping of the robot's work environment is embedded in the robot's memory. According to the experiment's results, the mobile robot's differential drive can pass through existing obstacles. In this research, four test environments represent different obstacles in each environment. The track length is 1.5 meters. The robot's tolerance to the goal is 0.1 m, so when the robot is in the 1.41 m position, the robot's speed is 0 rpm. The safe distance between the robot and the obstacle is 0.2 m, so the robot will find a route to get away from the obstacle when the robot reaches that safe distance. The speed of the resulting robot decreases as the distance between the robot and the destination gets closer according to the differential drive kinematics equation of the mobile robot.