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Journal : Faktor Exacta

PROTOTYPE SISTEM KENDALI ROBOT ARM GRIPPER MANIPULATOR MENGGUNAKAN FLEX SENSOR DAN MPU6050 BERBASIS INTERNET OF THINGS Habib Nurfaizal; Makhsun Makhsun; Yan Mitha Djaksana
Faktor Exacta Vol 13, No 4 (2020)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v13i4.6598

Abstract

In this sophisticated era a lot of human work that has begun to be done by robots. Robots are used to facilitate work that can not be done by humans, such as moving an item in a dangerous place. One of the robots created to facilitate human work is a robot that has a shape like a human arm called the arm gripper manipulator. Arm gripper manipulator is a robot that has the ability to move like a human arm. The manipulator arm consists of joint, link, and end-effector. This research designed a control system of the robot arm gripper manipulator with 2 modes, gesture mode and IoT mode. The microcontroller used is Arduino Mega 2560 with flex sensor control and MPU 6050 inertia measurement unit sensor in gesture mode and IoT control mode with time average errors in 5 movements is 2.08%. The overall test results of the robot arm gripper manipulator can be controlled with gesture mode and IoT mode.Abstract. In this sophisticated era a lot of human work that has begun to be done by robots. Robots are used to facilitate work that can not be done by humans, such as moving an item in a dangerous place. One of the robots created to facilitate human work is a robot that has a shape like a human arm called the arm gripper manipulator. Arm gripper manipulator is a robot that has the ability to move like a human arm. The manipulator arm consists of joint, link, and end-effector. This research designed a control system of the robot arm gripper manipulator with 2 modes, gesture mode and IoT mode. The microcontroller used is Arduino Mega 2560 with flex sensor control and MPU 6050 inertia measurement unit sensor in gesture mode and IoT control mode with time average errors in 5 movements is 2.08%. The overall test results of the robot arm gripper manipulator can be controlled with gesture mode and IoT mode.