Skripsi

PERANCANGAN SISTEM AVOIDING HALANG RINTANG HUMANOID ROBOT MENGGUNAKAN SENSOR LIDAR BERBASIS FUZZY LOGIC

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Penilaian

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In general, the notion of robots can be associated with living things in the form of human or animal movements made of several metal elements and driven by electric power. There are several types of robots today, such as wheeled, legged, and humanoid robots. The robot is controlled manually and automatically. In controlling the automatic robot, an avoiding system is needed so that the robot does not hit the obstacles in front of it. So, in this study, a wheeled humanoid robot was developed that uses the Sugeno Fuzzy Logic method and the LIDAR A1 sensor as software and hardware in the obstacle-avoiding system. Sugeno's Fuzzy Logic is an algorithm system that has a constant output. Thus, the wheeled human robot can avoid obstacles quickly and accurately. The results obtained from this study are the obstacle avoiding system shows good results, as evidenced by several tests where when the first test of obstacle avoiding with 7 membership functions the LIDAR sensor can avoid obstacles with a percentage of 100%, in the second test with 5 membership functions the robot can do obstacle avoiding with a percentage of 96%, and in the third test with 3 membership functions the robot can do obstacle avoiding with a percentage of 86.67%. with the position of obstacles in the robot’s front, left, and right. It can be concluded that the more membership functions are used, the more stable and accurate the results will be.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2207002358	T74870	T748702022	Central Library (Referens)	Available

Detail Information

Series Title

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Call Number

T748702022

Publisher

Indralaya : Prodi Teknik Elektro, Fakultas Teknik Universitas Sriwijaya., 2022

Collation

v, 55 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

629.807

Content Type

Text

Media Type

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Carrier Type

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Edition

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Subject(s)

Teknik elektro
Teknik Kontrol Otomatis, Robot

Specific Detail Info

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Statement of Responsibility

MURZ

Other version/related

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