Noise-Suppressing Newton Algorithm for Kinematic Control of Robots
In this paper, armed with the integral control method, a new noise-suppressing Newton (NSN) algorithm is proposed for the redundancy resolution of redundant robot manipulators efficiently. For practical hardware implementation, the discrete-time noise-suppressing Newton (abbreviated as DTNSN) algori...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8818630/ |
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| author | Xiuchun Xiao Lin Wei Dongyang Fu Jingwen Yan Huan Wang |
| author_facet | Xiuchun Xiao Lin Wei Dongyang Fu Jingwen Yan Huan Wang |
| author_sort | Xiuchun Xiao |
| collection | DOAJ |
| description | In this paper, armed with the integral control method, a new noise-suppressing Newton (NSN) algorithm is proposed for the redundancy resolution of redundant robot manipulators efficiently. For practical hardware implementation, the discrete-time noise-suppressing Newton (abbreviated as DTNSN) algorithm is discretized from the continues NSN algorithm. Specifically, the distinguishing feature of the proposed DTNSN algorithm is that it can rigorously converge with inherent tolerance to noises induced by communication jamming and computational systematical errors. In contrast, considerable traditional algorithms often dispose of noises with the high-degree filter from the viewpoint of signal processing, which requires a complex system structure and further results in a heavy computational burden. Note that theoretical analyses are provided to elaborate the convergent property of the DTNSN algorithm polluted with constant bias, time-dependent linear noises and bounded random noises. Besides, by the proposed DTNSN algorithm, the end effector of both serial and parallel redundant robot manipulators complete the allocated motion planning and are impervious to the noisy simulated environment. |
| format | Article |
| id | doaj-art-dda48cc96bd64fcea51edc09571f605c |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-dda48cc96bd64fcea51edc09571f605c2025-08-20T03:55:48ZengIEEEIEEE Access2169-35362025-01-011312429512430210.1109/ACCESS.2019.29376868818630Noise-Suppressing Newton Algorithm for Kinematic Control of RobotsXiuchun Xiao0https://orcid.org/0000-0002-3389-6689Lin Wei1Dongyang Fu2https://orcid.org/0000-0003-0426-4356Jingwen Yan3https://orcid.org/0000-0002-6153-3519Huan Wang4https://orcid.org/0000-0001-6884-9682College of Electronic and Information Engineering, Guangdong Ocean University, Zhanjiang, ChinaSchool of Information Science and Engineering, Lanzhou University, Lanzhou, ChinaCollege of Electronic and Information Engineering, Guangdong Ocean University, Zhanjiang, ChinaCollege of Electronic Engineering, Shantou University, Shantou, ChinaCollege of Electronic and Information Engineering, Guangdong Ocean University, Zhanjiang, ChinaIn this paper, armed with the integral control method, a new noise-suppressing Newton (NSN) algorithm is proposed for the redundancy resolution of redundant robot manipulators efficiently. For practical hardware implementation, the discrete-time noise-suppressing Newton (abbreviated as DTNSN) algorithm is discretized from the continues NSN algorithm. Specifically, the distinguishing feature of the proposed DTNSN algorithm is that it can rigorously converge with inherent tolerance to noises induced by communication jamming and computational systematical errors. In contrast, considerable traditional algorithms often dispose of noises with the high-degree filter from the viewpoint of signal processing, which requires a complex system structure and further results in a heavy computational burden. Note that theoretical analyses are provided to elaborate the convergent property of the DTNSN algorithm polluted with constant bias, time-dependent linear noises and bounded random noises. Besides, by the proposed DTNSN algorithm, the end effector of both serial and parallel redundant robot manipulators complete the allocated motion planning and are impervious to the noisy simulated environment.https://ieeexplore.ieee.org/document/8818630/Noise-suppressing Newton algorithmredundancy resolutionserial redundant robot manipulatorsparallel redundant robot manipulators |
| spellingShingle | Xiuchun Xiao Lin Wei Dongyang Fu Jingwen Yan Huan Wang Noise-Suppressing Newton Algorithm for Kinematic Control of Robots IEEE Access Noise-suppressing Newton algorithm redundancy resolution serial redundant robot manipulators parallel redundant robot manipulators |
| title | Noise-Suppressing Newton Algorithm for Kinematic Control of Robots |
| title_full | Noise-Suppressing Newton Algorithm for Kinematic Control of Robots |
| title_fullStr | Noise-Suppressing Newton Algorithm for Kinematic Control of Robots |
| title_full_unstemmed | Noise-Suppressing Newton Algorithm for Kinematic Control of Robots |
| title_short | Noise-Suppressing Newton Algorithm for Kinematic Control of Robots |
| title_sort | noise suppressing newton algorithm for kinematic control of robots |
| topic | Noise-suppressing Newton algorithm redundancy resolution serial redundant robot manipulators parallel redundant robot manipulators |
| url | https://ieeexplore.ieee.org/document/8818630/ |
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