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Title:Daljinsko voden robot z zaznavanjem ovir na računalniku Raspberry Pi 3 B
Authors:ID Zajc, Aljaž (Author)
ID Holobar, Aleš (Mentor) More about this mentor... New window
Files:.pdf UN_Zajc_Aljaz_2019.pdf (1,68 MB)
MD5: F8DDA8D21C6CD79837776D207C5343D7
PID: 20.500.12556/dkum/037cb42b-f371-493a-9b08-4132e3f93b92
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V diplomskem delu opisujemo izdelavo avtonomnega robota, ki zaznava ovire. Preučili smo delovanje operacijskega sistema ROS in njegove interakcije z računalnikom Raspberry Pi 3 B. Za implementacijo robota smo uporabili dva gonilnika BTS7960B, štiri elektromotorje, računalnik Raspberry Pi 3 B, igralni plošček F710 ter senzor Rplidar A1M8. Igralni plošček smo uporabili za daljinsko upravljanje robota, izogibanje oviram pa smo implementirali s pomočjo signalov senzorja Rplidar A1M8. V ta namen smo razvili algoritem za izogibanje ovir AZ19, ki robotu omogoča avtonomno vožnjo. Na koncu smo učinkovitost robotove vožnje predstavili v namensko zgrajenem poligonu.
Keywords:ROS, Raspberry Pi, robot, avtonomna vožnja
Place of publishing:Maribor
Publisher:[A. Zajc]
Year of publishing:2019
PID:20.500.12556/DKUM-73173 New window
UDC:007.52(043.2)
COBISS.SI-ID:22240790 New window
NUK URN:URN:SI:UM:DK:OYUUHJE6
Publication date in DKUM:27.03.2019
Views:2389
Downloads:291
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:27.02.2019

Secondary language

Language:English
Title:Remote-Controlled obstacle detecting robot running on Raspberry Pi 3 B
Abstract:The goal of the thesis was to make an autonomous robot, which is able to detect obstacles on its way. We examined the capabilities of ROS operating system and its interaction with the Raspberry Pi 3 B computer. For implementation of the robot, we used two BTS7960B drivers, four electric motors, a Raspberry Pi 3 B computer, F710 Wireless Gamepad and a Rplidar A1M8 sensor. We used gamepad to remotely control the robot. Data from Rplidar was used to develop AZ19 algorithm for obstacles avoidance, which enables the robot to drive autonomously. We tested the robot performance in the custom-made polygon.
Keywords:ROS, Raspberry Pi, robot, autonomous driving


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