Human-Robot Interaction Using Reinforcement Learning and Convolutional Neural Network

Human-Robot Interaction Using Reinforcement Learning and Convolutional Neural Network

Proper interaction is a crucial aspect of team collaborations for successfully achieving a common goal. In recent times, more technically advanced robots have been introduced into the industrial environments sharing the same workspace as other robots and humans which causes the need for human-robot...

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Bibliographic Details
Main Authors: Khan, Yousuf, Otalvaro, Edier
Format: Others
Language:English
Published: Mälardalens högskola, Akademin för innovation, design och teknik 2020
Subjects:
Robotics
Robotteknik och automation
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-50918
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spelling ndltd-UPSALLA1-oai-DiVA.org-mdh-509182020-10-06T05:28:02ZHuman-Robot Interaction Using Reinforcement Learning and Convolutional Neural NetworkengKhan, YousufOtalvaro, EdierMälardalens högskola, Akademin för innovation, design och teknikMälardalens högskola, Akademin för innovation, design och teknik2020RoboticsRobotteknik och automationProper interaction is a crucial aspect of team collaborations for successfully achieving a common goal. In recent times, more technically advanced robots have been introduced into the industrial environments sharing the same workspace as other robots and humans which causes the need for human-robot interaction (HRI) to be greater than ever before. The purpose of this study is to enable a HRI by teaching a robot to classify different human facial expressions as either positive or negative using a convolutional neural network and respond to each of them with the help of the reinforcement learning algorithm Q-learning.The simulation showed that the robot could accurately classify and react to the facial expressions under the instructions given by the Q-learning algorithm. The simulated results proved to be consistent in every conducted experiment having low variances. These results are promising for future research to allow for the study to be conducted in real-life environments. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-50918application/pdfinfo:eu-repo/semantics/openAccess
collection NDLTD
language English
format Others
sources NDLTD
topic Robotics
Robotteknik och automation
spellingShingle Robotics
Robotteknik och automation
Khan, Yousuf
Otalvaro, Edier
Human-Robot Interaction Using Reinforcement Learning and Convolutional Neural Network
description Proper interaction is a crucial aspect of team collaborations for successfully achieving a common goal. In recent times, more technically advanced robots have been introduced into the industrial environments sharing the same workspace as other robots and humans which causes the need for human-robot interaction (HRI) to be greater than ever before. The purpose of this study is to enable a HRI by teaching a robot to classify different human facial expressions as either positive or negative using a convolutional neural network and respond to each of them with the help of the reinforcement learning algorithm Q-learning.The simulation showed that the robot could accurately classify and react to the facial expressions under the instructions given by the Q-learning algorithm. The simulated results proved to be consistent in every conducted experiment having low variances. These results are promising for future research to allow for the study to be conducted in real-life environments.
author Khan, Yousuf
Otalvaro, Edier
author_facet Khan, Yousuf
Otalvaro, Edier
author_sort Khan, Yousuf
title Human-Robot Interaction Using Reinforcement Learning and Convolutional Neural Network
title_short Human-Robot Interaction Using Reinforcement Learning and Convolutional Neural Network
title_full Human-Robot Interaction Using Reinforcement Learning and Convolutional Neural Network
title_fullStr Human-Robot Interaction Using Reinforcement Learning and Convolutional Neural Network
title_full_unstemmed Human-Robot Interaction Using Reinforcement Learning and Convolutional Neural Network
title_sort human-robot interaction using reinforcement learning and convolutional neural network
publisher Mälardalens högskola, Akademin för innovation, design och teknik
publishDate 2020
url http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-50918
work_keys_str_mv AT khanyousuf humanrobotinteractionusingreinforcementlearningandconvolutionalneuralnetwork
AT otalvaroedier humanrobotinteractionusingreinforcementlearningandconvolutionalneuralnetwork
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