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master's thesis
Sigurnosni sustav za prepoznavanje ljudi u radnom prostoru robota zasnovan na AdaBoost algoritmu i stroju s potpornim vektorima
Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2021. urn:nbn:hr:200:474360
Šimundić, Valentin
Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Computer Engineering and Automation
Chair of Automation and Robotics

Institutional repository: Faculty of Electrical Engineering, Computer Science and Information Technology Osijek

Cite this document

Šimundić, V. (2021). Sigurnosni sustav za prepoznavanje ljudi u radnom prostoru robota zasnovan na AdaBoost algoritmu i stroju s potpornim vektorima (Master's thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek. Retrieved from https://urn.nsk.hr/urn:nbn:hr:200:474360

Šimundić, Valentin. "Sigurnosni sustav za prepoznavanje ljudi u radnom prostoru robota zasnovan na AdaBoost algoritmu i stroju s potpornim vektorima." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2021. https://urn.nsk.hr/urn:nbn:hr:200:474360

Šimundić, Valentin. "Sigurnosni sustav za prepoznavanje ljudi u radnom prostoru robota zasnovan na AdaBoost algoritmu i stroju s potpornim vektorima." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2021. https://urn.nsk.hr/urn:nbn:hr:200:474360

Šimundić, V. (2021). 'Sigurnosni sustav za prepoznavanje ljudi u radnom prostoru robota zasnovan na AdaBoost algoritmu i stroju s potpornim vektorima', Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 21 May 2024, https://urn.nsk.hr/urn:nbn:hr:200:474360

Šimundić V. Sigurnosni sustav za prepoznavanje ljudi u radnom prostoru robota zasnovan na AdaBoost algoritmu i stroju s potpornim vektorima [Master's thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2021 [cited 2024 May 21] Available at: https://urn.nsk.hr/urn:nbn:hr:200:474360

V. Šimundić, "Sigurnosni sustav za prepoznavanje ljudi u radnom prostoru robota zasnovan na AdaBoost algoritmu i stroju s potpornim vektorima", Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:200:474360

Metadata
TitleSigurnosni sustav za prepoznavanje ljudi u radnom prostoru robota zasnovan na AdaBoost algoritmu i stroju s potpornim vektorima
Title (english)Safety system for human detection in robot workspace based on AdaBoost algorithm and support vector machine
AuthorValentin Šimundić
MentorRobert Cupec (mentor)
Committee memberRobert Cupec (predsjednik povjerenstva)
Committee memberEmmanuel Karlo Nyarko (član povjerenstva)
Committee memberDamir Filko (član povjerenstva)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
(Department of Computer Engineering and Automation)
(Chair of Automation and Robotics)
Osijek
Defense date and country2021-07-19, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Electrical Engineering
Automation and Robotics
Abstract
U ovom diplomskom radu, predstavljen je sustav za upravljanje robotskim manipulatorom temeljen na prepoznavanju i praćenju ljudi. Rad je nastao kao dio projekta HDR (engl. Humans Detected by Robots) u suradnji s tvrtkom Danieli Systec d.o.o. Korišteni sustav za prepoznavanje i praćenje ljudi temelji se na AdaBoost algoritmu i stroju s potpornim vektorima, koristeći HOG deskriptore i Haar značajke. Robotski sustav sastoji se od robotskog manipulatora ABB-IRB 2400L, RGB-D kamere Microsoft Kinect v1 te ROS razvojnog okvira. Cjelokupni sustav implementiran je i ispitan na ROS Kinetic i ROS Melodic distribucijama. Eksperimentalna evaluacija provedena je na HDR skupu podataka, pri čemu su računati pokazatelji kakvoće odziv, preciznost i točnost. Provedena evaluacija odnosi se na testiranje detektora, predviđanja brzina i zaustavljanja robota. Najveća postignuta vrijednost odziva iznosi 87.5%, dok najveće vrijednosti preciznosti i točnosti iznose 100%. Rezultati variraju u ovisnosti o situaciji i vrsti testa.
Abstract (english)
In this thesis, a system for controlling robotic manipulators based on human detection and tracking is presented. The thesis was written as a part of the HDR (Humans Detected by Robots) project in cooperation with Danieli Systec. The system used for human detection and tracking is based on the AdaBoost algorithm and Support Vector Machines (SVM), using HOG descriptors and Haar features. The robotic system consists of an ABB-IRB 2400L robotic manipulator, a Microsoft Kinect v1 RGB-D camera, and ROS development framework. The entire system was implemented and tested on ROS Kinetic and ROS Melodic distributions. Experimental evaluation was performed on the HDR dataset with recall, precision, and accuracy used as metrics. The evaluation includes detector tests, speed prediction tests, and robot stopping tests. The highest achieved value of recall was 87.5%, while the highest value of precision and accuracy was 100%. The results vary depending on the situation and the type of test.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:200:474360
Study programmeTitle: Graduate University Study Programme in Computer Engineering
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2021-08-13 07:00:24