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Journal : J-Innovation

IMPLEMENTASI TRAJECTORY PLANNINGPADA ROBOT MANIPULATOR 4 DOF UNTUK MENCARI KEBOCORAN GAS Aditya P.P. Prasetyo; Rendyansyah; Kemahyanto Exaudi
J-Innovation Vol. 6 No. 2 (2017): Jurnal J-Innovation
Publisher : Politeknik Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (645.233 KB) | DOI: 10.55600/jipa.v6i2.38

Abstract

Gas leakage in industrial areas will have negative impacts such as air pollution, loss, or even disaster. The occurrence of leakage can be caused by corrosion or from the valve crack in the pipe, and so forth. Therefore, it is necessary to have a system that can monitor the state of the gas pipeline so the possibility of leakage can be known earlier. This research has developed application of robot manipulator 4 DOF integrated with gas sensor that is MQ4 which placed at end of robot arm. The method used to determine the motion of the robot is trajectory planning in the form of cubic trajectory, where in this method the robot movement route will adjust the pattern of pipelines in cartesian coordinates. To determine the possibility of a leak of butane gas, observed the output signal from the gas sensor. If it exceeds 3.5 volts then the coordinates passed by the end-effector may leak. The experimental results show that robot manipulators with cubic trajectory planning are able to track paths according to the shape of pipes, and gas leaks can be detected by gas sensors.
KENDALI GERAK ROBOT HEXAPOD MENGGUNAKAN REMOTE CONTROL BERBASIS ANDROID Rendyansyah; Huda Ubaya; Amrial Faydinar; Yurias Ramdhan
J-Innovation Vol. 7 No. 1 (2018): Jurnal J-Innovation
Publisher : Politeknik Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (484.066 KB) | DOI: 10.55600/jipa.v7i1.48

Abstract

The development of technology can help human work, one of which is robot technology that can be used in the military and security fields.As in the application of robot in the military field is a robot for investigating an arena or object. This robot is generally controlled using remote control and even the use of mini computer to monitor the unpredictable environment. In the other hand, the use of legged robot like the hexapod robot is also used to search target, investigation, and others. In this research, hexapod robot has been equipped with Arduino Uno module, servo motor driver, servo motors, and integrated with power supply. Hexapod robot is controlled manually using a remote control based on an Android smartphone, and the communication use Bluetooth. The robot has implanted the logic of movement forward, backward, turn right and left, which movement is active if given an order by the user using Android. For the robot move forward by sending the character "A", the robot move backward by sending the character "B", and to turn left and right respectively by sending the characters "C" and "D". The experimental results show that hexapod robot and android smartphone are connected properly, and the robot has successfully moveforward, backward, turn left and right according to the commands given to the robot.
Implementation of the K-Nearest Neighbor Algorithm on a 4-DoF Manipulator Robot for Color-Based Object Retrieval Rendyansyah, Rendyansyah; Irmawan; Hera Hikmarika; Caroline
J-Innovation Vol. 14 No. 2 (2025): Jurnal J Innovation
Publisher : Politeknik Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55600/jipa.v14i2.352

Abstract

This study discusses implementing the K-Nearest Neighbor (K-NN) algorithm on a 4-DoF manipulator robot to pick up objects based on color. The main objective of this study is to design and test a robot control system capable of automatically recognizing, picking up, and moving objects according to color classification. The color detection process is carried out using a camera that extracts color component values in RGB space, which are then classified using the K-NN algorithm with parameter k = 5. The classification results form the basis for the movement of the manipulator robot, which is controlled through cubic trajectory-based trajectory planning, so that the movement of each servo motor joint is smooth and coordinated. Testing was conducted 30 times with three object color categories: red, green, and blue. The experimental results showed that the system could classify colors and pick up objects with a success rate of 96%. Minor failures occurred due to lighting variations that affected color detection results. Overall, the results of this study indicate that the integration of the K-NN algorithm and cubic trajectory is effective in improving the performance of manipulator robots for color-based object recognition and picking tasks and has the potential to be applied in computer vision-based industrial automation systems.