IMPLEMENTASI HUMAN-MACHINE INTERACTION PADA SERVICE ROBOT BERBASIS INTEGRASI PERSEPSI DAN NAVIGASI

IZWANDA, AHMAD KARIM ABDURRAHMAN and Dwijayanti, Suci (2024) IMPLEMENTASI HUMAN-MACHINE INTERACTION PADA SERVICE ROBOT BERBASIS INTEGRASI PERSEPSI DAN NAVIGASI. Undergraduate thesis, Sriwijaya University.

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Abstract

Sistem yang digunakan pada servis robot terbagi menjadi beberapa subsistem dalam menjalankan tugasnya untuk melayani manusia. Subsistem itu dapat berupa kemampuan penginderaan serta aksi seperti yang dilakukan manusia pada umumnya. Masing-masing subsistem diperlukan sebuah pengintegrasian sehingga service robot dapat bekerja. Subsistem yang digunakan pada penelitian ini terdiri dari sistem navigasi, persepsi, dan komunikasi. Sistem navigasi menggunakan timed elastic band (TEB Local Planner), Sistem persepsi yang digunakan yaitu menggunakan model pelatihan convolutional neural network (CNN) dengan arsitektur VGG19 untuk pendeteksian wajah dan model pelatihan you only look once (YOLOv8), dan Sistem komunikasi yang digunakan menggunakan algoritma transformers dengan model whisper untuk speech to text, dan google text to speech (GTTS) untuk text to speech. Pengujian sistem terintegrasi ini dilakukan di dalam Laboratorium Kendali dan Robotika Universitas Sriwijaya dalam melakukan pengambilan objek, bersalaman, serta berkomunikasi dengan melakukan beberapa percobaan secara real-time. Hasil yang didapatkan menunjukkan bahwa tingkat kesuksesan sistem terintegrasi dalam melakukan pengambilan objek, bersalaman, dan berkomunikasi secara berurutan dengan persentase sebesar 40%, 70%, dan 75%. Hasil persentase percobaan pengambilan barang didapatkan sangat kecil karena sistem persepsi objek hanya dapat mendeteksi botol dan cangkir, sedangkan objek gelas dan solder belum dapat dideteksi. Sistem persepsi wajah yang digunakan belum baik karena adanya kesamaan ciri wajah yang dideteksinya, sehingga percobaan secara real-time masih belum akurat. Sistem navigasi yang digunakan berhasil dengan persentase 100% dalam bernavigasi dalam laboratorium, sehingga dapat disimpulkan bahwa sistem navigasi yang digunakan dapat bekerja dengan baik di dalam laboratorium The system used in service robot is divided into several subsystems in carrying out its duties to serve humans. This subsystem can be in the form of sensing abilities and actions like those carried out by humans in general. Each subsystem requires integration so that the service robot can work. The subsystems used in this research consist of navigation, perception and communication systems. The navigation system uses a timed elastic band (TEB Local Planner), the perception system used uses a convolutional neural network (CNN) training model with VGG19 architecture for face detection and a you only look once (YOLOv8) training model, and the communication system used uses a transformers algorithm with a whisper model for speech to text, and google text to speech (GTTS) for text to speech. Testing of this integrated system was carried out in the Sriwijaya University Control and Robotics Laboratory by retrieving objects, shaking hands and communicating by carrying out several real-time experiments. The results obtained show that the success rate of the integrated system in retrieving objects, shaking hands and communicating sequentially is 40%, 70% and 75%. The percentage of retrieving object trials was very small because the object perception system could only detect bottles and cups, while glass and solder objects could not be detected. The facial perception system used is not good because the facial features it detects are similar, so real-time experiments are still not accurate. The navigation system used was successful with a percentage of 100% in navigating in the laboratory, so it can be concluded that the navigation system used can work well in the laboratory.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	service robot, navigasi, persepsi, komunikasi, CNN, YOLOv8, whisper, GTTS, transformers, timed elastic band
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1-9971 Electrical engineering. Electronics. Nuclear engineering > TK1 Electrical engineering--Periodicals. Automatic control--Periodicals. Computer science--Periodicals. Information technology--Periodicals. Automatic control. Computer science. Electrical engineering. Information technology.
Divisions:	03-Faculty of Engineering > 20201-Electrical Engineering (S1)
Depositing User:	Ahmad Karim Abdurrahman Izwanda
Date Deposited:	18 Jul 2024 02:14
Last Modified:	18 Jul 2024 02:14
URI:	http://repository.unsri.ac.id/id/eprint/151471

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