Kendali Pesawat Nirawak Berbasis Sinyal Otot Lengan

Lemppa, Andi Fytra Khaliva (2023) Kendali Pesawat Nirawak Berbasis Sinyal Otot Lengan. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Dengan berkembangnya industri, kebutuhan untuk dapat mengkontrol pesawat nirawak se- makin bertambah. Pesawat nirawak dapat membantu kehidupan sehari-hari manusia seperti mengantarkan suplai dan barang yang bersifat penting. Untuk dapat mengintegerasikan pe- sawat nirawak kedalam kehidupan sehari-hari manusia, perangkat untuk dapat mengkontrol drone diperlukan untuk dapat digunakan setiap saat saat dibutuhkan. Untuk meraih hal ini perangkat kendali pesawat tidak hanya perlu dapat mudah dibawa bepergian namun juga dapat dikenakan sehingga dapat dipakai kapanpun saat dibutuhkan. Dengan menggunakan machine learning perangkat kontrol pesawat nirawak dapat diperkecil dan dikenakan. Sensor Electro Myo-graph merupakan sensor yang mengukur perbedaan potensi otot listrik sehingga perangkat kontrol pesawat dapat dikontrol dengan menggunakan sinyal otot untuk membentuk gestur. Gestur dari sinyal EMG ini dapat diklasifikasikan sehingga pesawat dapat mengenali perintah dari pengguna berdasarkan gestur. Hal ini dapat diraih dengan mengenali pola sinyal gestur menggunakan LSTM. Dengan menggunakan LSTM untuk mengenali gestur, pengguna dapat melakukan navigasi sederhadana pada pesawat seperti menggerakkan pesawat nirawak untuk maju, berputar 180°, dan bergerak kesamping.
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With Unmanned Aerial Vehicle or UAV becoming a more common means of delivering supply of even delivering critical equipment, the need of control to integrate UAV as part of daily humans life is crucial. With the importance of air as a means of transportation UAV gave humanity a way to solve a problem without actually putting a human into dangerous labour. Integrating UAV into human lives means that human need to be able to control UAV at a moment notice, to achieve this a device to control UAV not only need to be light, but also wearable so anyone can operate a UAV with a fingertips away. Using Electro Myo-graph or known as EMG sensor, it is possible to not only control UAV with wearable device but also controlling it with a gesture by recognizing a gesture pattern of arm muscle signal produced by EMG sensor using machine learning. One of the many sensor that available are Myo Armband that not only can serves as an EMG sensor but also wearable. Recognizing pattern of muscle signal can be achieved by using LSTM. Classifying a gesture can give us a way to control uAV by signing a command based on the current gesture that the user are doing, it can also give the ability for a user to navigate basic move command to navigate UAV such as, move straight, make a circle turn, and also roll

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Pesawat nirawak, kontrol, gestur, EMG, pembelajaran mesin, LSTM
Subjects:	T Technology > TJ Mechanical engineering and machinery T Technology > TJ Mechanical engineering and machinery > TJ211 Robotics. T Technology > TJ Mechanical engineering and machinery > TJ211.4 Robot motion T Technology > TJ Mechanical engineering and machinery > TJ211.415 Mobile robots
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Computer Engineering > 90243-(S1) Undergraduate Thesis
Depositing User:	Andi Fytra Khaliva Lemppa
Date Deposited:	07 Aug 2023 01:05
Last Modified:	04 Dec 2023 07:52
URI:	http://repository.its.ac.id/id/eprint/101596

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