Indoor navigation system using quick response code technology
Date of Publication
2013
Document Type
Bachelor's Thesis
Degree Name
Bachelor of Science in Electronics and Communications Engineering
Subject Categories
Communication | Electrical and Electronics | Engineering
College
Gokongwei College of Engineering
Department/Unit
Electronics and Communications Engineering
Thesis Adviser
Alan B. Landa
Defense Panel Chair
Edwin Sybingco
Defense Panel Member
Argel A. Bandala
Enrique M. Manzano
Abstract/Summary
This study focused on the use of Quick Response (QR) codes for navigation and delivery of a mobile robot, and the usage of Raspberry Pi as the Central Processing Unit of the system. With a web application which can command the robot to navigate and deliver to a certain location identified by QR codes and stored in a database, the Raspberry Pi reads this command and carries out the instructions of a Python-based program by performing arithmetic, logical, and input/output operations of the system for the mobile robot to successfully navigate and deliver. Through the cameras connected to it, the Raspberry Pi decodes the QR codes and determines if there is a match between the data sent by the web application and the scanned value. Whether there is a match or none, the Raspberry Pi communicates to the PICI6F877A microcontroller through its General-Purpose Input/Output (GPIO) pins for the movement of the robot. The GPIO pins, which will give an output of 3.3 volts to supply the input ports of the microcontroller, will be determined by and dependent on the sensor readings connected to and sent by the microcontroller to the other GPIO pins as well. Overall, the Raspberry Pi and the scanned QR Code values, with the use of a web application and sensor readings, control and dictate the mobile robots movement for navigation and the Tormax motors movement for delivery.
Abstract Format
html
Language
English
Format
Accession Number
TU18196
Shelf Location
Archives, The Learning Commons, 12F, Henry Sy Sr. Hall
Physical Description
xxvii, 234 leaves : illustrations (some colored) ; 28 cm.
Keywords
Compressed sensing (Telecommunication); Optical character recognition; QR codes; Raspberry Pi (Computer)
Recommended Citation
Balbuena, J. F., Barcenilla, G. O., Barrion, B. M., Nuestro, A. P., & Santos, M. M. (2013). Indoor navigation system using quick response code technology. Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/10823
Embargo Period
2-4-2022
