Dimasa sekarang ini robot banyak digunakan dalam berbagai bidang kehidupan, terdapat berbagai jenis robot yang dikembangkan salah satunya adalah robot lengan karena memiliki fungsi yang sama dengan lengan manusia. Salah satu kendala dalam pengoperasian robot adalah karena kebanyakan robot memerlukan pemrograman terlebih dahulu untuk mengoperasikan sehingga sulit bagi orang awam. Tujuan dari penelitian ini adalah membuat sistem kendali lengan robot yang dapat mengendalikan lengan robot hanya dengan menggerakan tangan dan menekan tombol. Penelitian ini menggunakan sensor MPU-6050 sebagai sensor sudut dan potensiometer sebagai pengatur gerakan robot, selain itu juga menggunakan Arduino Uno sebagai pengolah masukan sensor agar dapat mengendalikan lengan robot. Adapun robot yang digunakan adalah robot lengan 4 DOF (Degree Of Freedom) dengan penggerak motor servo. Penelitian ini menggunakan metode research and development yaitu dengan mempelajari dan mengembangkan penelitian sebelumnya. Pengujian sensor MPU-6050 mendapatkan hasil dengan nilai error pembacaan sebesar 0,72% pada sumbu X dan 0,68% pada sumbu Y. Waktu yang dibutuhkan untuk sekali proses pemindahan barang adalah selama 3 detik. Hasil dari sistem yang telah dibuat, robot mampu memindahkan barang ketempat yang diinginkan. Tingkat keberhasilan proses pindah barang menggunakan robot lengan 4 DOF adalah 100%.
A prosthetic hand is an artificial device that resembles a human hand which can help the human with a physical disability. Previously, the development of a prosthetic hand is designed in various method, from passive to bionic. Electrooculography (EOG) is a technique for measuring potential differences between the front (positive pole formed by the cornea) and the back (negative pole formed by the retina) of the eyeball which can be used to detect eye movements. The purpose of this study is to design a prosthetic hand with two degrees (2D) of freedom using EOG based control. This system consists of electrodes, EOG amplifier, Bluetooth transmitter-receiver, servo motors, and hand prosthetics. In this study, the system will recognize the eye movements, namely front, right, left, up, and down. The system will recognize the motion based on a threshold value. In the hardware implementation, the system was composed of five electrode sensors which installed around the eye, instrumentation amplifier, high pass filter, low pass filter, noninverting amplifier, summing amplifier, a notch filter circuit, and Arduino UNO microcontroller. In EOG data acquisition, this study involved ten healthy subjects. After the evaluation with five trial for each motion, the error for each eye movement is 0%, 0%, 36%, 4% and 16% for right, left, top, bottom, and front, respectively. This study provided an alternative method to control a prosthetics hand with good performance.
In the development of technology in the current era is one of the most rapid progress, it is marked by almost all managers of data and information has been done with the computer because of the increasingly diverse information issues handled, Detection of objects is one of the most important early stages before Done object recognition process. Eye blink detection can be used to open a new file or an application. In this research use case detection eye blinking on video using OpenCV to open notepad application. The blink detection uses the haar cascade classifier method for realtime detection and the OpenCV Library. The first step determines the pattern 1111100000. Next enter the video sample avi format to match with a predetermined pattern. In this program the system managed to detect the eye according to the pattern by circling the eye area when the eyes are open or literate and when the eyes closed or brake there is no circle in the eye area for the correct video sample.
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