Firmansyah, Riza Agung (2015) Sistem Auto Docking Pada Service Robot Menggunakan Persepsi Visual. Masters thesis, Institut Technology Sepuluh Nopember.
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Abstract
Sistem auto docking adalah sebuah sistem pada sebuah robot yang berfungsi untuk
melakukan pengisian baterai secara otomatis. Sistem ini dijalankan saat robot
mendeteksi tegangan kerja minimal. Robot melakukan pengisian baterai pada
sebuah docking station. Sistem auto docking ini dibangun dengan menggunakan
persepsi visual berbasis local binary pattern (LBP) histogram matching agar robot
mampu mendeteksi docking station. Setelah pendeteksian berhasil, dilanjutkan
dengan ekstraksi fitur untuk mendapatkan posisi dan orientasi docking station.
Selanjutnya posisi dan orientasi dijadikan sebagai informasi masukan fuzzy logic
controller untuk menjalankan robot. Robot menjalankan sistem auto docking
menggunakan persepsi visual saat tegangan baterai dibawah 23.6 volt dan
menghentikan pengisian baterai saat tegangan baterai diatas 26.4 volt. Pengisian
baterai dilakukan dalam waktu 135 menit. Sistem auto docking mampu bekerja
dengan tingkat akurasi 86.7 % dan optimal pada rentang luminasi 116 lux hingga
395 lux. Robot melakukan penyambungan konektor dengan rata-rata waktu 53.78
detik dari jarak 450 cm dengan akurasi penyambungan konektor mencapai 84%.
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Auto docking system is a system on a robot that has a function to make the battery
charging automatically. This system is executed when the robot detects a minimum
working voltage. Robot perform battery charging on a docking station. Auto
docking system was built using visual perception based on local binary pattern
(LBP) histogram matching to detect a docking station. After docking station
detected, then feature extraction is performed to get the posistion and orientation of
the docking station. Position and orientation is used as fuzzy logic controller input
to move the robot. Robot executed the auto docking system using visual perception
when the battery voltage is below 23.6 volts and finish charging the battery when
voltage is over 26.4 volts. Battery charging is done within 135 minutes. Auto
docking system using visual perception has an accuration 86.7% and optimally
work at luminance 116 lux up to 395 lux. The robot is able to perform splicing
connector with an average time of 53.78 seconds from a distance of 450 cm with an
accuracy of 84%.
| Item Type: | Thesis (Masters) |
|---|---|
| Additional Information: | RTE 629.892 Fir s |
| Uncontrolled Keywords: | service robot, auto docking, persepsi visual, local binary pattern, histogram matching, fuzzy logic controller. |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Industrial Technology > Electrical Engineering > 20101-(S2) Master Thesis |
| Depositing User: | Mr. Tondo Indra Nyata |
| Date Deposited: | 06 Nov 2018 03:21 |
| Last Modified: | 06 Nov 2018 03:21 |
| URI: | http://repository.its.ac.id/id/eprint/59938 |
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