IMPLEMENTASI METODE WEIGHTLESS NEURAL NETWORK UNTUK SISTEM NAVIGASI BERBASIS GPS ROBOT PENGANTAR OBAT

HUTAHAEAN, EBENEZER and Zarkasi, Ahmad and Sembiring, Sarmayanta (2025) IMPLEMENTASI METODE WEIGHTLESS NEURAL NETWORK UNTUK SISTEM NAVIGASI BERBASIS GPS ROBOT PENGANTAR OBAT. Undergraduate thesis, Sriwijaya University.

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Abstract

This study designed and implemented a navigation system for a medicine delivery robot based on Arduino Uno R3, integrating GPS for goal seeking and a Weightless Neural Network (WNN) for obstacle avoidance. The robot successfully reached the target coordinates with an average accuracy of 2.20 m and completed 8 out of 10 navigation trials in a controlled environment. The WNN was implemented using five infrared sensors connected to pins A0–A4, where analog data were converted into binary form to serve as inputs for generating output patterns that control DC motors via a driver connected to pins 5–10. Memory optimization through sensor data reduction to 4-bit Most Significant Bit (MSB) decreased RAM usage up to 98.4375% without reducing the robot’s ability to recognize environmental patterns.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Robot pengantar obat, Navigasi berbasis GPS, Weightless Neural Network, Arduino Uno R3, Optimasi Memori
Subjects:	R Medicine > R Medicine (General) > R858-859.7 Computer applications to medicine. Medical informatics T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7885-7895 Computer engineering. Computer hardware
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Ebenezer Hutahaean
Date Deposited:	22 Oct 2025 08:46
Last Modified:	22 Oct 2025 08:46
URI:	http://repository.unsri.ac.id/id/eprint/185310

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