A Review of Motion Planning Algorithms for Robotic Arm Systems

Shuai Liu; Pengcheng Liu

A Review of Motion Planning Algorithms for Robotic Arm Systems

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Motion planning plays a vital role in the field of robotics. This paper discusses the latest advancements made in the research and development of various algorithms and approaches in motion planning in the past five years, with a strong focus on robotic arm systems. Most of the recent motion planning algorithms are based on random sampling algorithms. More effective algorithms such as optimization-based, Probabilistic Movement Primitives (ProMPs)-based and physics-based methods are feasible research directions to explore to improve the effectiveness. The evaluation benchmarking of the algorithm is a worthy research direction. The model-based methods can improve the efficiency of the task, but it has less ability to deal with accidents. In contrast, model-free methods can solve this problem, but it takes a long time to compute. This paper also provides an insight into the robotic manipulation of rigid and non-rigid (deformable) objects is explored. Based on the study, some challenges and future research trends are summarized, and some algorithms and approaches are suggested for the most efficient use of the robotic arms.

Original language	English
Title of host publication	8th International Conference on Robot Intelligence Technology and Applications (proceedings)
Publisher	IEEE
Publication status	Accepted/In press - 15 Nov 2020
Event	The 8th International Conference on Robot Intelligence Technology and Applications - Cardiff, Cardiff, United Kingdom Duration: 11 Dec 2020 → 13 Dec 2020

Conference

Conference	The 8th International Conference on Robot Intelligence Technology and Applications
Country/Territory	United Kingdom
City	Cardiff
Period	11/12/20 → 13/12/20

Bibliographical note

This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details.

Access to Document

A Review of Motion Planning Algorithms for Robotic Arm Systems
This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details.
Accepted author manuscript, 260 KB

Cite this

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title = "A Review of Motion Planning Algorithms for Robotic Arm Systems",

abstract = "Motion planning plays a vital role in the field of robotics. This paper discusses the latest advancements made in the research and development of various algorithms and approaches in motion planning in the past five years, with a strong focus on robotic arm systems. Most of the recent motion planning algorithms are based on random sampling algorithms. More effective algorithms such as optimization-based, Probabilistic Movement Primitives (ProMPs)-based and physics-based methods are feasible research directions to explore to improve the effectiveness. The evaluation benchmarking of the algorithm is a worthy research direction. The model-based methods can improve the efficiency of the task, but it has less ability to deal with accidents. In contrast, model-free methods can solve this problem, but it takes a long time to compute. This paper also provides an insight into the robotic manipulation of rigid and non-rigid (deformable) objects is explored. Based on the study, some challenges and future research trends are summarized, and some algorithms and approaches are suggested for the most efficient use of the robotic arms.",

author = "Shuai Liu and Pengcheng Liu",

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T1 - A Review of Motion Planning Algorithms for Robotic Arm Systems

AU - Liu, Shuai

AU - Liu, Pengcheng

N1 - This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details.

PY - 2020/11/15

Y1 - 2020/11/15

N2 - Motion planning plays a vital role in the field of robotics. This paper discusses the latest advancements made in the research and development of various algorithms and approaches in motion planning in the past five years, with a strong focus on robotic arm systems. Most of the recent motion planning algorithms are based on random sampling algorithms. More effective algorithms such as optimization-based, Probabilistic Movement Primitives (ProMPs)-based and physics-based methods are feasible research directions to explore to improve the effectiveness. The evaluation benchmarking of the algorithm is a worthy research direction. The model-based methods can improve the efficiency of the task, but it has less ability to deal with accidents. In contrast, model-free methods can solve this problem, but it takes a long time to compute. This paper also provides an insight into the robotic manipulation of rigid and non-rigid (deformable) objects is explored. Based on the study, some challenges and future research trends are summarized, and some algorithms and approaches are suggested for the most efficient use of the robotic arms.

AB - Motion planning plays a vital role in the field of robotics. This paper discusses the latest advancements made in the research and development of various algorithms and approaches in motion planning in the past five years, with a strong focus on robotic arm systems. Most of the recent motion planning algorithms are based on random sampling algorithms. More effective algorithms such as optimization-based, Probabilistic Movement Primitives (ProMPs)-based and physics-based methods are feasible research directions to explore to improve the effectiveness. The evaluation benchmarking of the algorithm is a worthy research direction. The model-based methods can improve the efficiency of the task, but it has less ability to deal with accidents. In contrast, model-free methods can solve this problem, but it takes a long time to compute. This paper also provides an insight into the robotic manipulation of rigid and non-rigid (deformable) objects is explored. Based on the study, some challenges and future research trends are summarized, and some algorithms and approaches are suggested for the most efficient use of the robotic arms.

M3 - Conference contribution

BT - 8th International Conference on Robot Intelligence Technology and Applications (proceedings)

PB - IEEE

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Y2 - 11 December 2020 through 13 December 2020

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