A Gradient Neural Network for online Solving the Time-varying Inverse Kinematics Problem of Four-wheel Mobile Robotic Arm
dc.contributor.author | Zhou, Y | |
dc.contributor.author | Liu, K | |
dc.contributor.author | Li, Chunxu | |
dc.contributor.author | Wang, G | |
dc.contributor.author | Liu, Y | |
dc.contributor.author | Sun, Z | |
dc.date.accessioned | 2021-06-30T11:26:47Z | |
dc.date.available | 2021-06-30T11:26:47Z | |
dc.date.issued | 2021-05-14 | |
dc.identifier.isbn | 9781665424233 | |
dc.identifier.issn | 2767-9861 | |
dc.identifier.uri | http://hdl.handle.net/10026.1/17287 | |
dc.description | No embargo required. | |
dc.description.abstract |
In this paper, a gradient neural network (GNN) is presented, analyzed and discussed to solve the time-varying inverse kinematics solution of the four-wheel mobile robotic arm, which can approximate the time varying inverse kinematics solution. A monolithic kinematics model of mobile robotic arm is established, and the inverse kinematics solution can synchronously coordinate the control of the mobile platform and the robotic arm to accomplish the task of the end-executor. Besides, the computer numerical results are provided to attest validity and high exactitude of GNN model in settling the time-varying inverse kinematics of a four-wheel mobile robotic arm. | |
dc.format.extent | 391-396 | |
dc.language.iso | en | |
dc.publisher | IEEE | |
dc.title | A Gradient Neural Network for online Solving the Time-varying Inverse Kinematics Problem of Four-wheel Mobile Robotic Arm | |
dc.type | conference | |
dc.type | Conference Proceeding | |
plymouth.date-start | 2021-05-14 | |
plymouth.date-finish | 2021-05-16 | |
plymouth.volume | 00 | |
plymouth.publisher-url | https://ieeexplore.ieee.org/document/9455633 | |
plymouth.conference-name | 2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS) | |
plymouth.publication-status | Published | |
plymouth.journal | 2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS) | |
dc.identifier.doi | 10.1109/ddcls52934.2021.9455633 | |
plymouth.organisational-group | /Plymouth | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering/School of Engineering, Computing and Mathematics | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA/UoA11 Computer Science and Informatics | |
plymouth.organisational-group | /Plymouth/Users by role | |
plymouth.organisational-group | /Plymouth/Users by role/Academics | |
dcterms.dateAccepted | 2021-06-25 | |
dc.rights.embargodate | 2021-7-2 | |
dc.identifier.eissn | 2767-9861 | |
dc.rights.embargoperiod | Not known | |
rioxxterms.versionofrecord | 10.1109/ddcls52934.2021.9455633 | |
rioxxterms.licenseref.uri | http://www.rioxx.net/licenses/all-rights-reserved | |
rioxxterms.licenseref.startdate | 2021-05-14 | |
rioxxterms.type | Conference Paper/Proceeding/Abstract |