Structure diagram of branched PUS with errors.
<div><p>Kinematic calibration is essential for improving the absolute accuracy of parallel robots, but conventional identification methods often struggle with the complex, non-linear coupling of their numerous geometric error parameters. This can lead to convergence to local rather than...
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2025
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| _version_ | 1852017094221103104 |
|---|---|
| author | Zesheng Wang (15244172) |
| author2 | Yanbiao Li (22170014) Bo Chen (32294) Kexin Ding (8739855) Jialong Zhu (1834288) Min Zhuang (218356) |
| author2_role | author author author author author |
| author_facet | Zesheng Wang (15244172) Yanbiao Li (22170014) Bo Chen (32294) Kexin Ding (8739855) Jialong Zhu (1834288) Min Zhuang (218356) |
| author_role | author |
| dc.creator.none.fl_str_mv | Zesheng Wang (15244172) Yanbiao Li (22170014) Bo Chen (32294) Kexin Ding (8739855) Jialong Zhu (1834288) Min Zhuang (218356) |
| dc.date.none.fl_str_mv | 2025-09-02T17:30:13Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0330675.g004 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Structure_diagram_of_branched_PUS_with_errors_/30033737 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biotechnology Plant Biology Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified selected uniformly throughout robot &# 8217 finite difference method eliminate error sources actuator displacement errors rpur parallel robot positional accuracy across kinematical error analysis global optimization strategy experimental results demonstrate overall pose error penalty function approach calibration methodology based sensitivity analysis parallel robots objective function identification results global optima absolute accuracy workspace using three recent screw theory performed using paper proposes onboard imu novel self negligible impact moving platform measurement points measurement data local rather linear coupling linear constraints kinematic chain joint encoders inverse kinematics handled using established based entire workspace benchmark comparison autonomous calibration |
| dc.title.none.fl_str_mv | Structure diagram of branched PUS with errors. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <div><p>Kinematic calibration is essential for improving the absolute accuracy of parallel robots, but conventional identification methods often struggle with the complex, non-linear coupling of their numerous geometric error parameters. This can lead to convergence to local rather than global optima, limiting the effectiveness of the calibration. To address this challenge, this paper proposes a novel self-calibration methodology based on a global optimization strategy. Taking the 5PUS-RPUR parallel robot as an example, its inverse kinematics is established based on screw theory. A sensitivity analysis is performed using the finite difference method to screen for and eliminate error sources with a negligible impact on the moving platform’s pose. Measurement points are then selected uniformly throughout the workspace using the farthest point sampling algorithm. An objective function for the GA is constructed by integrating the actuator displacement errors from each kinematic chain with the overall pose error of the moving platform. Non-linear constraints are handled using a penalty function approach. Based on measurement data from an onboard IMU and joint encoders, the identification results are obtained. The experimental results demonstrate that the proposed method significantly improves the robot’s positional accuracy across its entire workspace. The superiority and efficacy of this approach are further corroborated by a benchmark comparison with three recent, state-of-the-art calibration methodologies.</p></div> |
| eu_rights_str_mv | openAccess |
| id | Manara_40f3cc792f60ca40df3cd80bbee0ef8a |
| identifier_str_mv | 10.1371/journal.pone.0330675.g004 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30033737 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Structure diagram of branched PUS with errors.Zesheng Wang (15244172)Yanbiao Li (22170014)Bo Chen (32294)Kexin Ding (8739855)Jialong Zhu (1834288)Min Zhuang (218356)BiotechnologyPlant BiologySpace ScienceBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedselected uniformly throughoutrobot &# 8217finite difference methodeliminate error sourcesactuator displacement errorsrpur parallel robotpositional accuracy acrosskinematical error analysisglobal optimization strategyexperimental results demonstrateoverall pose errorpenalty function approachcalibration methodology basedsensitivity analysisparallel robotsobjective functionidentification resultsglobal optimaabsolute accuracyworkspace usingthree recentscrew theoryperformed usingpaper proposesonboard imunovel selfnegligible impactmoving platformmeasurement pointsmeasurement datalocal ratherlinear couplinglinear constraintskinematic chainjoint encodersinverse kinematicshandled usingestablished basedentire workspacebenchmark comparisonautonomous calibration<div><p>Kinematic calibration is essential for improving the absolute accuracy of parallel robots, but conventional identification methods often struggle with the complex, non-linear coupling of their numerous geometric error parameters. This can lead to convergence to local rather than global optima, limiting the effectiveness of the calibration. To address this challenge, this paper proposes a novel self-calibration methodology based on a global optimization strategy. Taking the 5PUS-RPUR parallel robot as an example, its inverse kinematics is established based on screw theory. A sensitivity analysis is performed using the finite difference method to screen for and eliminate error sources with a negligible impact on the moving platform’s pose. Measurement points are then selected uniformly throughout the workspace using the farthest point sampling algorithm. An objective function for the GA is constructed by integrating the actuator displacement errors from each kinematic chain with the overall pose error of the moving platform. Non-linear constraints are handled using a penalty function approach. Based on measurement data from an onboard IMU and joint encoders, the identification results are obtained. The experimental results demonstrate that the proposed method significantly improves the robot’s positional accuracy across its entire workspace. The superiority and efficacy of this approach are further corroborated by a benchmark comparison with three recent, state-of-the-art calibration methodologies.</p></div>2025-09-02T17:30:13ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0330675.g004https://figshare.com/articles/figure/Structure_diagram_of_branched_PUS_with_errors_/30033737CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/300337372025-09-02T17:30:13Z |
| spellingShingle | Structure diagram of branched PUS with errors. Zesheng Wang (15244172) Biotechnology Plant Biology Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified selected uniformly throughout robot &# 8217 finite difference method eliminate error sources actuator displacement errors rpur parallel robot positional accuracy across kinematical error analysis global optimization strategy experimental results demonstrate overall pose error penalty function approach calibration methodology based sensitivity analysis parallel robots objective function identification results global optima absolute accuracy workspace using three recent screw theory performed using paper proposes onboard imu novel self negligible impact moving platform measurement points measurement data local rather linear coupling linear constraints kinematic chain joint encoders inverse kinematics handled using established based entire workspace benchmark comparison autonomous calibration |
| status_str | publishedVersion |
| title | Structure diagram of branched PUS with errors. |
| title_full | Structure diagram of branched PUS with errors. |
| title_fullStr | Structure diagram of branched PUS with errors. |
| title_full_unstemmed | Structure diagram of branched PUS with errors. |
| title_short | Structure diagram of branched PUS with errors. |
| title_sort | Structure diagram of branched PUS with errors. |
| topic | Biotechnology Plant Biology Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified selected uniformly throughout robot &# 8217 finite difference method eliminate error sources actuator displacement errors rpur parallel robot positional accuracy across kinematical error analysis global optimization strategy experimental results demonstrate overall pose error penalty function approach calibration methodology based sensitivity analysis parallel robots objective function identification results global optima absolute accuracy workspace using three recent screw theory performed using paper proposes onboard imu novel self negligible impact moving platform measurement points measurement data local rather linear coupling linear constraints kinematic chain joint encoders inverse kinematics handled using established based entire workspace benchmark comparison autonomous calibration |