Trajectory optimization of high-speed robotic positioning with suppressed motion jerk via improved chicken swarm algorithm Article Swipe
YOU?
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· 2023
· Open Access
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· DOI: https://doi.org/10.21203/rs.3.rs-1909719/v1
To address the problems of premature convergence and low solution accuracy of the basic swarm optimization algorithm an improved chicken swarm algorithm based on parallel strategy and dynamic constraints (PDCSO) is proposed for the rooster update method with a parallel strategy while introducing X-best guidance and Levy flight step; dynamic constraints are given for the rooster followed by the hen, and the optimal rooster position is introduced, which improves the convergence accuracy while avoiding falling into local optimum. The simulation experiments on 18 classical test functions show that the PDCSO algorithm outperforms other comparative algorithms in terms of convergence speed, solution accuracy and solution stability. In addition, PDCSO is applied to robotic arm trajectory optimization by fitting the joint trajectory with 5 times B-sample curve, and after algorithm optimization and simulation verification in ADAMS, it is proved that PDCSO can effectively reduce the running time and motion shock of robotic arm and improve the execution efficiency of robotic arm.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-1909719/v1
- https://www.researchsquare.com/article/rs-1909719/latest.pdf
- OA Status
- gold
- Cited By
- 3
- References
- 13
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4319738858
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4319738858Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.21203/rs.3.rs-1909719/v1Digital Object Identifier
- Title
-
Trajectory optimization of high-speed robotic positioning with suppressed motion jerk via improved chicken swarm algorithmWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-02-09Full publication date if available
- Authors
-
Yankun Li, Yuyang Lu, Dongya Li, Rui Li, Chonghai Xu, Xiaozhi Gao, Yu LiuList of authors in order
- Landing page
-
https://doi.org/10.21203/rs.3.rs-1909719/v1Publisher landing page
- PDF URL
-
https://www.researchsquare.com/article/rs-1909719/latest.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.researchsquare.com/article/rs-1909719/latest.pdfDirect OA link when available
- Concepts
-
Jerk, Swarm behaviour, Trajectory, Computer science, Control theory (sociology), Motion (physics), Artificial intelligence, Algorithm, Computer vision, Acceleration, Physics, Control (management), Astronomy, Classical mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
3Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2, 2023: 1Per-year citation counts (last 5 years)
- References (count)
-
13Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.test | 85 |
| abstract_inverted_index.that | 88, 138 |
| abstract_inverted_index.time | 145 |
| abstract_inverted_index.with | 38, 121 |
| abstract_inverted_index.PDCSO | 90, 108, 139 |
| abstract_inverted_index.after | 127 |
| abstract_inverted_index.based | 23 |
| abstract_inverted_index.basic | 14 |
| abstract_inverted_index.given | 53 |
| abstract_inverted_index.joint | 119 |
| abstract_inverted_index.local | 77 |
| abstract_inverted_index.other | 93 |
| abstract_inverted_index.shock | 148 |
| abstract_inverted_index.step; | 49 |
| abstract_inverted_index.swarm | 15, 21 |
| abstract_inverted_index.terms | 97 |
| abstract_inverted_index.times | 123 |
| abstract_inverted_index.which | 68 |
| abstract_inverted_index.while | 42, 73 |
| abstract_inverted_index.ADAMS, | 134 |
| abstract_inverted_index.X-best | 44 |
| abstract_inverted_index.curve, | 125 |
| abstract_inverted_index.flight | 48 |
| abstract_inverted_index.method | 37 |
| abstract_inverted_index.motion | 147 |
| abstract_inverted_index.proved | 137 |
| abstract_inverted_index.reduce | 142 |
| abstract_inverted_index.speed, | 100 |
| abstract_inverted_index.update | 36 |
| abstract_inverted_index.(PDCSO) | 30 |
| abstract_inverted_index.address | 2 |
| abstract_inverted_index.applied | 110 |
| abstract_inverted_index.chicken | 20 |
| abstract_inverted_index.dynamic | 28, 50 |
| abstract_inverted_index.falling | 75 |
| abstract_inverted_index.fitting | 117 |
| abstract_inverted_index.improve | 153 |
| abstract_inverted_index.optimal | 63 |
| abstract_inverted_index.robotic | 112, 150, 158 |
| abstract_inverted_index.rooster | 35, 56, 64 |
| abstract_inverted_index.running | 144 |
| abstract_inverted_index.B-sample | 124 |
| abstract_inverted_index.accuracy | 11, 72, 102 |
| abstract_inverted_index.avoiding | 74 |
| abstract_inverted_index.followed | 57 |
| abstract_inverted_index.guidance | 45 |
| abstract_inverted_index.improved | 19 |
| abstract_inverted_index.improves | 69 |
| abstract_inverted_index.optimum. | 78 |
| abstract_inverted_index.parallel | 25, 40 |
| abstract_inverted_index.position | 65 |
| abstract_inverted_index.problems | 4 |
| abstract_inverted_index.proposed | 32 |
| abstract_inverted_index.solution | 10, 101, 104 |
| abstract_inverted_index.strategy | 26, 41 |
| abstract_inverted_index.addition, | 107 |
| abstract_inverted_index.algorithm | 17, 22, 91, 128 |
| abstract_inverted_index.classical | 84 |
| abstract_inverted_index.execution | 155 |
| abstract_inverted_index.functions | 86 |
| abstract_inverted_index.premature | 6 |
| abstract_inverted_index.algorithms | 95 |
| abstract_inverted_index.efficiency | 156 |
| abstract_inverted_index.simulation | 80, 131 |
| abstract_inverted_index.stability. | 105 |
| abstract_inverted_index.trajectory | 114, 120 |
| abstract_inverted_index.comparative | 94 |
| abstract_inverted_index.constraints | 29, 51 |
| abstract_inverted_index.convergence | 7, 71, 99 |
| abstract_inverted_index.effectively | 141 |
| abstract_inverted_index.experiments | 81 |
| abstract_inverted_index.introduced, | 67 |
| abstract_inverted_index.introducing | 43 |
| abstract_inverted_index.outperforms | 92 |
| abstract_inverted_index.optimization | 16, 115, 129 |
| abstract_inverted_index.verification | 132 |
| abstract_inverted_index.<title>Abstract</title> | 0 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5076917019 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 7 |
| corresponding_institution_ids | https://openalex.org/I111599522 |
| citation_normalized_percentile.value | 0.60691047 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |