Title:	Implement of a 6-DOF manipulator with machine vision and machine learning algorithms
Authors:	Chen, Pi-Yun Chen, Wei-Lun Pai, Neng-Sheng Chou, Min-Hung Huang, Guo-Shing Chang, Che-Yuan
Citation:	2017 International Conference on Applied Electronics: Pilsen, 5th – 6th September 2017, Czech Republic, p.59-64.
Issue Date:	2017
Publisher:	Západočeská univerzita v Plzni
Document type:	konferenční příspěvek conferenceObject
URI:	http://hdl.handle.net/11025/35409
ISBN:	978–80–261–0641–8 (Print) 978–80–261–0642–5 (Online)
ISSN:	1805–9597 (Online) 1803–7232 (Print)
Keywords:	strojové vidění;invariantní transformace prvků;Kinect;strojové učení;posílení učení;manipulátor
Keywords in different language:	machine vision;scale-invariant feature transform;Kinect;machine learning;reinforcement learning;manipulator
Abstract in different language:	This paper explores the application of a Machine Vision and Machine Learning Algorithm to a Manipulator with six degrees of freedom (6-DOF). A Kinect sensor were used to extract images from a screen and obtain the relevant target information. Image processing was accomplished using a Scale-invariant feature transform (SIFT) Algorithm to capture image of the target object. The processed visual is rendered on the computer controller and Manipulator Learning is accomplished using a Reinforcement Learning Algorithm. Markov Decision Processes (MDP) were used to train the Manipulator to move to the location of the target object. Experimental results showed the Reinforcement Learning Algorithm proposed in this paper is effective and can be utilized on a 6-DOF Manipulator with reproducible results.
Rights:	© Západočeská univerzita v Plzni
Appears in Collections:	Applied Electronics 2017 Applied Electronics 2017

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