Jurusan Teknik Elektro

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    Transformasi Sistem Koordinat Lokal dan Global Pada Robot Mecanum Wheels
    (Politeknik Negeri Batam, 2018-07-20) Sholeh, Muhammad Syaifudin; Soebhakti, Hendawan
    Mobile Robot consisting of four wheels Mecanum Wheel Drive can move by translating and rotating to the desired direction by using kinematic inverse equation. But the kinematic inverse equation is one of the things that still coordinate local as a reference for its movement. Robot movement still can not be used to achieve the goal because it coordinates the robot is always dynamic or follow where the direction of the robot moves. So in this research will be used method that can access local coordinate become global coordinate robot with coordinate transformation. The expected result of this research is the movement of robot and can move in the form of visualization. From the research that has been done the robot can move in accordance with the direction of the instructed when the output motor speed that has been described kinematik inverse does not exceed the maximum speed limit of the motor used. The maximum speed of motor used is 124 rpm. The error occurs because the system is still open loop
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    Pengenalan Suara Terhadap Pergerakan Robot Beroda dengan Metode FFT
    (Politeknik Negeri Batam, 2018-06-04) Bayu, Krisina; Risandriya, Sumantri K.; Fatekha, Rifqi Amalya
    Speech Recognition to Mobile Robot Movement With FFT Method is a system that serves to move the robot direction based on the given sound. Usually to move a wheeled robot someone is still using the PC or remote control. With these problems researchers create a software system and hardware designed to recognize human voice commands. The voice signal will be processed on PC using FFT (Fast Fourier Transform) method in LabVIEW to find out the amplitude and frequency. Then to know the features of advanced sound, turn right and turn left using MFCC (Mel Frequency Cepstrum Coefficients) method then the result of these characteristics is converted into time domain then stored into reference template by DTW (Dynamic Time Warping) method. The experimental results show that the system can recognize forward sound, turn right, and turn left has an average success rate of 81.1% and has an average error of 18.8%. Sound recognition errors are caused because when the speech sounds forward, turn right, and turn left the environment is not always quiet.
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    Robot Pendeteksi Manusia Menggunakan Sensor PIR
    (Politeknik Negeri Batam, 2018-06-06) Rusdi, Muhammad Ibnu; Pamungkas, Daniel Sutopo
    The higher the crime rate and also the rate of economic growth is slowing, causing a growing need for a surveillance system in the room. This surveillance system to anticipate the level of criminality such as theft, etc. Therefore the author making a tool that is: Human Detection Robots Using Sensor PIR, the Robot serving as supervisor of security which will make it easier for security officers in night shift. The workings of this robot will follow the walls of the left so that the robot is able to surround all the system navigation can use Ultrasonic sensors. The robot will be able to detect the presence of human beings through his movements using a PIR sensor help. Then the robot will send a warning to the security supervisor in the form of sound the alarm through the system interfacenya on android. Where the robot and allows supervisors to communicate in real time. Expected to design this tool later can help in terms of oversight.
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    Sistem Pengenalan dan Tracking Wajah pada Robot 2 DOF
    (Politeknik Negeri Batam, 2018-06-06) Al-Aidid, Sayed Maulana Iqbal; Pamungkas, Daniel Sutopo
    Face recognition needs accurate software system to get the optimally funcion in recognizing a human face with scanning. The system able to determine human face when detected. It’s has the same characteristics with faces in the database. In other sides, face tracking, face detection and face recognition is the priority. The method Haarcascade is used to detect the face on image or input from the camera and face recognition method is used Local Binery Pattern Histogram. The robot will know face owner’s if the face in the detection and input of the camera has the same characteristic as the pictures of face in the database. This system able to detect multiple faces in single frame. And also, the movement of the camera is able to follow the movement of the face. But have to make straight projecting position between face and camera.
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    3DoF Kinematik Robot Lengan
    (Politeknik Negeri Batam, 2017) Nugroho, Dionisius Adji; Soebhakti, Hendawan ; Toar, Handri
    This research contains of design in 3 Degree of Freedom (DoF) robotic arm, which was a small prototype of robot industry. The design of this research to simulate the actual movements of the robot industry. This robotic arm designed with kinematics using forward kinematics and inverse kinematics by showing the movement of any DoF. This design includes the mechanical design model and available to control with microcontroller by using Arduino UNO. Each DoF are driven by DC motor which is controlled by using microcontroller. This application of robot arm is connected using a Graphical User Interface (GUI) Visual C# with calculation data covers kinematics. The result of this research obtained the lowest error percentage at special angle movements in the process of inverse kinematics at θ1, θ2 amounting to 0% of 0.011% and θ3 of 0.233%. While in the process forward kinematics retrieved the value of the error in x, y of 0%, and z of 0.39%.