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Review of learning-based robotic manipulation in cluttered environments

Robotic manipulation refers to how robots intelligently interact with the objects in their surroundings, such as grasping and carrying an object from one place to another. Dexterous manipulating skills enable robots to assist humans in accomplishing various tasks that might be too dangerous or diffi...

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Main Authors:	Mohammed, Marwan Qaid, Kwek, Lee Chung, Chua, Shing Chyi, Al-Dhaqm, Arafat Mohammed Rashad, Nahavandi, Saeid, Elfadil Eisa, Taiseer Abdalla, Miskon, Muhammad Fahmi, Al-Mhiqani, Mohammed Nasser, Ali, Abdulalem, Mohammed Abaker, Mohammed Abaker, Alandoli, Esmail Ali
Format:	Article
Language:	English
Published:	MDPI 2022
Subjects:	QA75 Electronic computers. Computer science TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/104051/1/ArafatMohammedRashad2022_ReviewofLearningBasedRobotic.pdf http://eprints.utm.my/104051/ http://dx.doi.org/10.3390/s22207938
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spelling	my.utm.1040512024-01-14T00:55:42Z http://eprints.utm.my/104051/ Review of learning-based robotic manipulation in cluttered environments Mohammed, Marwan Qaid Kwek, Lee Chung Chua, Shing Chyi Al-Dhaqm, Arafat Mohammed Rashad Nahavandi, Saeid Elfadil Eisa, Taiseer Abdalla Miskon, Muhammad Fahmi Al-Mhiqani, Mohammed Nasser Ali, Abdulalem Mohammed Abaker, Mohammed Abaker Alandoli, Esmail Ali QA75 Electronic computers. Computer science TK Electrical engineering. Electronics Nuclear engineering Robotic manipulation refers to how robots intelligently interact with the objects in their surroundings, such as grasping and carrying an object from one place to another. Dexterous manipulating skills enable robots to assist humans in accomplishing various tasks that might be too dangerous or difficult to do. This requires robots to intelligently plan and control the actions of their hands and arms. Object manipulation is a vital skill in several robotic tasks. However, it poses a challenge to robotics. The motivation behind this review paper is to review and analyze the most relevant studies on learning-based object manipulation in clutter. Unlike other reviews, this review paper provides valuable insights into the manipulation of objects using deep reinforcement learning (deep RL) in dense clutter. Various studies are examined by surveying existing literature and investigating various aspects, namely, the intended applications, the techniques applied, the challenges faced by researchers, and the recommendations adopted to overcome these obstacles. In this review, we divide deep RL-based robotic manipulation tasks in cluttered environments into three categories, namely, object removal, assembly and rearrangement, and object retrieval and singulation tasks. We then discuss the challenges and potential prospects of object manipulation in clutter. The findings of this review are intended to assist in establishing important guidelines and directions for academics and researchers in the future. MDPI 2022-10-18 Article PeerReviewed application/pdf en http://eprints.utm.my/104051/1/ArafatMohammedRashad2022_ReviewofLearningBasedRobotic.pdf Mohammed, Marwan Qaid and Kwek, Lee Chung and Chua, Shing Chyi and Al-Dhaqm, Arafat Mohammed Rashad and Nahavandi, Saeid and Elfadil Eisa, Taiseer Abdalla and Miskon, Muhammad Fahmi and Al-Mhiqani, Mohammed Nasser and Ali, Abdulalem and Mohammed Abaker, Mohammed Abaker and Alandoli, Esmail Ali (2022) Review of learning-based robotic manipulation in cluttered environments. Sensors, 22 (20). pp. 1-37. ISSN 1424-8220 http://dx.doi.org/10.3390/s22207938 DOI:10.3390/s22207938
institution	Universiti Teknologi Malaysia
building	UTM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Malaysia
content_source	UTM Institutional Repository
url_provider	http://eprints.utm.my/
language	English
topic	QA75 Electronic computers. Computer science TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	QA75 Electronic computers. Computer science TK Electrical engineering. Electronics Nuclear engineering Mohammed, Marwan Qaid Kwek, Lee Chung Chua, Shing Chyi Al-Dhaqm, Arafat Mohammed Rashad Nahavandi, Saeid Elfadil Eisa, Taiseer Abdalla Miskon, Muhammad Fahmi Al-Mhiqani, Mohammed Nasser Ali, Abdulalem Mohammed Abaker, Mohammed Abaker Alandoli, Esmail Ali Review of learning-based robotic manipulation in cluttered environments
description	Robotic manipulation refers to how robots intelligently interact with the objects in their surroundings, such as grasping and carrying an object from one place to another. Dexterous manipulating skills enable robots to assist humans in accomplishing various tasks that might be too dangerous or difficult to do. This requires robots to intelligently plan and control the actions of their hands and arms. Object manipulation is a vital skill in several robotic tasks. However, it poses a challenge to robotics. The motivation behind this review paper is to review and analyze the most relevant studies on learning-based object manipulation in clutter. Unlike other reviews, this review paper provides valuable insights into the manipulation of objects using deep reinforcement learning (deep RL) in dense clutter. Various studies are examined by surveying existing literature and investigating various aspects, namely, the intended applications, the techniques applied, the challenges faced by researchers, and the recommendations adopted to overcome these obstacles. In this review, we divide deep RL-based robotic manipulation tasks in cluttered environments into three categories, namely, object removal, assembly and rearrangement, and object retrieval and singulation tasks. We then discuss the challenges and potential prospects of object manipulation in clutter. The findings of this review are intended to assist in establishing important guidelines and directions for academics and researchers in the future.
format	Article
author	Mohammed, Marwan Qaid Kwek, Lee Chung Chua, Shing Chyi Al-Dhaqm, Arafat Mohammed Rashad Nahavandi, Saeid Elfadil Eisa, Taiseer Abdalla Miskon, Muhammad Fahmi Al-Mhiqani, Mohammed Nasser Ali, Abdulalem Mohammed Abaker, Mohammed Abaker Alandoli, Esmail Ali
author_facet	Mohammed, Marwan Qaid Kwek, Lee Chung Chua, Shing Chyi Al-Dhaqm, Arafat Mohammed Rashad Nahavandi, Saeid Elfadil Eisa, Taiseer Abdalla Miskon, Muhammad Fahmi Al-Mhiqani, Mohammed Nasser Ali, Abdulalem Mohammed Abaker, Mohammed Abaker Alandoli, Esmail Ali
author_sort	Mohammed, Marwan Qaid
title	Review of learning-based robotic manipulation in cluttered environments
title_short	Review of learning-based robotic manipulation in cluttered environments
title_full	Review of learning-based robotic manipulation in cluttered environments
title_fullStr	Review of learning-based robotic manipulation in cluttered environments
title_full_unstemmed	Review of learning-based robotic manipulation in cluttered environments
title_sort	review of learning-based robotic manipulation in cluttered environments
publisher	MDPI
publishDate	2022
url	http://eprints.utm.my/104051/1/ArafatMohammedRashad2022_ReviewofLearningBasedRobotic.pdf http://eprints.utm.my/104051/ http://dx.doi.org/10.3390/s22207938
_version_	1789424371080626176
score	13.211869

Review of learning-based robotic manipulation in cluttered environments

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