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Energy-saving trajectory planning for robots using the genetic algorithm with assistant chromosomes

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Abstract

Fossil fuel depletion and global warming are becoming increasingly important problems. Many trajectory plans for robot manipulators are developed by prioritizing operation efficiency, such as operating time and controllability, without considering energy consumption. In this study, the energy consumption problem is examined. This study discusses the application of a genetic algorithm (GA) to solve the problem of minimizing the energy consumption of a robot manipulator with nonlinear friction in the joints. The GA can search a wide area for an optimal solution; however, a long computation time is required. A gradient method can be used to quickly find a solution; however, the solution has a high probability of being a local optimum. This paper proposes a method that combines a gradient method and GA to quickly determine an optimal solution. In addition, the validity of the proposed method is examined.

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Authors and Affiliations

  1. Department of Electrical Engineering and Information Science, National Institute of Technology, Kure College, 2-2-11 Agaminami, Kure, Hiroshima, 737-8506, Japan

    Yoshio Yokose

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  1. Yoshio Yokose
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Correspondence to Yoshio Yokose.

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This work was presented in part at the 24th International Symposium on Artificial Life and Robotics (Beppu, Oita, January 23–25, 2019).

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Yokose, Y. Energy-saving trajectory planning for robots using the genetic algorithm with assistant chromosomes. Artif Life Robotics 25, 89–93 (2020). https://doi.org/10.1007/s10015-019-00556-8

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  • DOI: https://doi.org/10.1007/s10015-019-00556-8

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