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Energy Saving Planner Model via Differential Evolutionary Algorithm for Bionic Palletizing Robot.
Deng, Yi; Zhou, Tao; Zhao, Guojin; Zhu, Kuihu; Xu, Zhaixin; Liu, Hai.
Afiliação
  • Deng Y; School of Electronic and Electrical Engineering, Wuhan Textile University, Wuhan 430200, China.
  • Zhou T; Department of Research and Development, TBEA Co., Ltd., Changji 100089, China.
  • Zhao G; School of Electronic and Electrical Engineering, Wuhan Textile University, Wuhan 430200, China.
  • Zhu K; School of Electronic and Electrical Engineering, Wuhan Textile University, Wuhan 430200, China.
  • Xu Z; School of Electronic and Electrical Engineering, Wuhan Textile University, Wuhan 430200, China.
  • Liu H; Department of Research and Development, TBEA Co., Ltd., Changji 100089, China.
Sensors (Basel) ; 22(19)2022 Oct 05.
Article em En | MEDLINE | ID: mdl-36236645
ABSTRACT
Energy saving in palletizing robot is a fundamental problem in the field of industrial robots. However, the palletizing robot often suffers from the problems of high energy consumption and lacking flexibility. In this work, we introduce a novel differential evolution algorithm to address the adverse effects caused by the instability of the initial trajectory parameters while reducing the energy. Specially, a simplified analytical model of the palletizing robot is firstly developed. Then, the simplified analytical model and the differential evolutionary algorithm are combined to form a planner with the goal of reducing energy consumption. The energy saving planner optimizes the initial parameters of the trajectories collected by the bionic demonstration system, which in turn enables a reduction in the operating power consumption of the palletizing robot. The major novelty of this article is the use of a differential evolutionary algorithm that can save the energy consumption as well as boosting its flexibility. Comparing with the traditional algorithms, the proposed method can achieve the state-of-the-art performance. Simulated and actual experimental results illustrate that the optimized trajectory parameters can effectively reduce the energy consumption of palletizing robot by 16%.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Robótica Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Robótica Idioma: En Ano de publicação: 2022 Tipo de documento: Article