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A novel artificial bee colony algorithm for inverse kinematics calculation of 7-DOF serial manipulators

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Abstract

In order to overcome the complexity in solving the inverse kinematics calculation of 7-DOF serial manipulator, a new approach CPABC based on artificial bee colony (ABC) algorithm is proposed. CPABC uses the chaotic mapping to optimize the population distribution of the initial food sources to get rid of the local optimization. The whole group of food sources in CPABC is divided into several subgroups which evolve independently and communicate with each other at a certain frequency to improve the convergence rate. To balance the global and local exploitation, two control parameters are introduced to adjust the search step and the change frequency of the optimization parameter when searching the new food source. CPABC is applied to the inverse kinematics calculation of 7-DOF serial manipulator. the simulation results show that CPABC has stronger global searching ability and more fast convergence rate than that of other ABC algorithms.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China under Grant [No. 61573145], the Public Research and Capacity Building of Guangdong Province under Grant [No. 2014B010104001] and the Basic and Applied Basic Research of Guangdong Province under Grant [No. 2015A03030 8018], and the authors greatly thank these grants.

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Authors and Affiliations

  1. School of Computer Science and Engineering, South China University of Technology, 382 Zhonghuan Road East, Panyu District, Guangzhou, People’s Republic of China

    Li Zhang & Nanfeng Xiao

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  1. Li Zhang
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  2. Nanfeng Xiao
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Correspondence to Li Zhang.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Communicated by V. Loia.

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Zhang, L., Xiao, N. A novel artificial bee colony algorithm for inverse kinematics calculation of 7-DOF serial manipulators. Soft Comput 23, 3269–3277 (2019). https://doi.org/10.1007/s00500-017-2975-y

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