Trajectory planning method of robot sorting system based on S-shaped acceleration/deceleration algorithm Article Swipe
Qizhi Chen
,
Chengrui Zhang
,
Hepeng Ni
,
Liang Xue
,
Haitao Wang
,
Tianliang Hu
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1177/1729881418813805
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1177/1729881418813805
To improve the sorting accuracy and efficiency of sorting system with large inertia robot, this article proposes a novel trajectory planning method based on S-shaped acceleration/deceleration algorithm. Firstly, a novel displacement segmentation method based on assumed maximum velocity is proposed to reduce the computational load of velocity planning. The sorting area can be divided into four parts by no more than three steps. Secondly, since the positions of workpieces are dynamically changing, a dynamic prediction method of workpiece picking position has been presented to consider all the possible positions of the robot and the workpiece, so as to realize the picking position prediction of the workpiece at any positions. Each situation in this method can constitute an equation with only one solution, and the existence of the solution can be verified by the proposed graphical method. The simulations of the motion time of the sorting process show that the proposed method can significantly shorten the sorting time and improve the sorting efficiency compared with the previous method. Finally, this method was applied to the Selective Compliance Assembly Robot Arm (SCARA) robot for experiments. In the physical picking experiment, the missing-pick rate was less than 1%, which demonstrates the efficiency and effectiveness of this method.
Related Topics
Concepts
Acceleration
Sorting
Computer science
SCARA
Trajectory
Inertia
Robot
Position (finance)
Displacement (psychology)
Process (computing)
Algorithm
Control theory (sociology)
Simulation
Artificial intelligence
Physics
Psychotherapist
Astronomy
Classical mechanics
Control (management)
Operating system
Psychology
Economics
Finance
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1177/1729881418813805
- https://journals.sagepub.com/doi/pdf/10.1177/1729881418813805
- OA Status
- gold
- Cited By
- 23
- References
- 8
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2901262610
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2901262610Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1177/1729881418813805Digital Object Identifier
- Title
-
Trajectory planning method of robot sorting system based on S-shaped acceleration/deceleration algorithmWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2018Year of publication
- Publication date
-
2018-11-01Full publication date if available
- Authors
-
Qizhi Chen, Chengrui Zhang, Hepeng Ni, Liang Xue, Haitao Wang, Tianliang HuList of authors in order
- Landing page
-
https://doi.org/10.1177/1729881418813805Publisher landing page
- PDF URL
-
https://journals.sagepub.com/doi/pdf/10.1177/1729881418813805Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://journals.sagepub.com/doi/pdf/10.1177/1729881418813805Direct OA link when available
- Concepts
-
Acceleration, Sorting, Computer science, SCARA, Trajectory, Inertia, Robot, Position (finance), Displacement (psychology), Process (computing), Algorithm, Control theory (sociology), Simulation, Artificial intelligence, Physics, Psychotherapist, Astronomy, Classical mechanics, Control (management), Operating system, Psychology, Economics, FinanceTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
23Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 4, 2023: 3, 2022: 6, 2021: 6Per-year citation counts (last 5 years)
- References (count)
-
8Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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