Hibridno upravljanje silom dodira za crtanje po ploči primjenom trajektorija s kontroliranim trzajem

master's thesis

• Title (english): Hybrid Force Control for Drawing on Board using Jerk-controlled Trajectories
• Author: Matko Kulaš
• Mentor: Zdenko Kovačić (mentor)
• Committee member: Zdenko Kovačić (predsjednik povjerenstva)
• Committee member: Stjepan Bogdan (član povjerenstva)
• Committee member: Matko Orsag (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2018-02-21, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Electrical Engineering

Abstract

U ovome radu napisani su algoritmi Taylor-ovog i Ho-Cook-ovog postupka, kao i transformacija koordinatnih sustava ploče u globalni koordinatni sustav. Svi algoritmi su isprobani u simulacijskom okruženju Matlab.

Nakon postavljanja novog paketa, na ROS platformi, za upravljanje robotskim sustavom Schunk LWA4P, napravljena je programska podrška za regulaciju sile pritiska robota te kretanje robota upravljano u stvarnom vremenu s regulacijom sile kroz željene točke prolaska. Iskorišteni su algoritmi strojnog učenja za uklanjanje statičke pogreške senzora sile.

Programska podrška je isprobana te je dala dobre rezultate.

Abstract (english)

In this document are written Taylor and Ho-Cook algorithms, and transformation of coordinate system of a board to global coordinate system. All algorithms are tested in simulation in Matlab.

After setting new package in ROS for controlling robot system of Schunk LWA4P, new application is made for force control and controlling robot in real time with force control through way-points. Machine learning algorithms have been used to resolve the problem of static error on force sensor.

Application is tested and it showed good results.

• Keywords: Schunk LWA4P; Matlab; Ho-Cook; Taylor; ROS; schunk canopen driver; fuzzy; kontrola trzaja; strojno učenje
• Keywords (english): Schunk LWA4P; Matlab; Ho-Cook; Taylor; ROS; schunk canopen driver; fuzzy; jerk control; machine learning
• Language: croatian
• URN:NBN: urn:nbn:hr:168:509787
• Study programme: Title: Electrical Engineering and Information Technology; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra inženjer/inženjerka elektrotehnike i informacijske tehnologije (magistar/magistra inženjer/inženjerka elektrotehnike i informacijske tehnologije)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2019-03-13 22:05:36