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An Energy Minimized Solution for Solving Redundancy of Underwater Vehicle-Manipulator System Based on Genetic Algorithm

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Advances in Swarm Intelligence (ICSI 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10385))

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Abstract

An energy minimized method using genetic algorithm for solving redundancy of underwater vehicle-manipulator system is proposed in this paper. Energy minimization is here set up as an optimization problem. Under the constraints of the dynamic and kinematic equations, the inverse kinematic solution with the optimal index is formed by using the weight pseudoinverse matrix. Energy consumption function is chosen as the objective function, and then the energy minimized solution based on genetic algorithm for solving the redundancy of the system is performed. Two numerical examples are carried out to verify the proposed method and promising result is obtained.

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Acknowledgments

This work is supported by the Key Basic Research Project of ‘Shanghai Science and Technology Innovation Plan’ (No. 15JC1403300), the National Natural Science Foundation of China (No. 61603277; No. 51579053), the State Key Laboratory of Robotics and Systems (Harbin Institute of Technology), key project (No. SKLRS-2015-ZD-03), and the SAST Project (No. 2016017). Meanwhile, this work is also partially supported by the Fundamental Research Funds for the Central Universities (No. 2014KJ032; ‘Interdisciplinary Project’ with No. 20153683), and ‘The Youth 1000 program’ project (No. 1000231901). It is also partially sponsored by ‘Shanghai Pujiang Program’ project (No. 15PJ1408400), the National College Students Innovation Project (No. 1000107094), as well as the project from Nuclear Power Engineering Co., Ltd. (No. 20161686). All these supports are highly appreciated.

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Authors and Affiliations

  1. Laboratory of Robotics and Multibody System, Tongji University, Shanghai, 201804, China

    Qirong Tang, Le Liang, Yinghao Li & Zhenqiang Deng

  2. University of Mining and Technology, Xuzhou, 221116, China

    Yinan Guo

  3. National Key Laboratory of Science and Technology on Underwater Vehicle, Harbin Engineering University, Harbin, 150001, China

    Hai Huang

Authors
  1. Qirong Tang
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  2. Le Liang
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  3. Yinghao Li
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  4. Zhenqiang Deng
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  5. Yinan Guo
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  6. Hai Huang
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Corresponding author

Correspondence to Qirong Tang .

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Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Kyushu University, Fukuoka, Japan

    Hideyuki Takagi

  3. Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

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Tang, Q., Liang, L., Li, Y., Deng, Z., Guo, Y., Huang, H. (2017). An Energy Minimized Solution for Solving Redundancy of Underwater Vehicle-Manipulator System Based on Genetic Algorithm. In: Tan, Y., Takagi, H., Shi, Y. (eds) Advances in Swarm Intelligence. ICSI 2017. Lecture Notes in Computer Science(), vol 10385. Springer, Cham. https://doi.org/10.1007/978-3-319-61824-1_43

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  • DOI: https://doi.org/10.1007/978-3-319-61824-1_43

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61823-4

  • Online ISBN: 978-3-319-61824-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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