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A Review on Optimization Methods to Enhance Energy Efficiency of Robots

EasyChair Preprint no. 1540

5 pagesDate: September 21, 2019

Abstract

The aim of this paper is to make available of a comprehensive review and to provide a reference of existing methodologies developed for enhancing of the energy efficiency of robots. In the present scenario of increased application of robots, the huge energy consumption is also being predicted. One of the possible solutions for energy consumption can be in terms of developing energy efficient robots. In the domain of energy efficient robot, different attempts are made in past, such as use of lightweight material, analysis of speed, identification of the least energy consuming trajectories and reduction of components weight by topology optimization, etc. The available methodologies to reduce the energy consumption of industrial robots are classified into two groups. The first group comprises of the different attempts of energy efficiency through trajectory optimization of the manipulator. Here, the energy required to perform a particular task is considered. The path is then optimized for minimum power consumption of the motors. This approach is applicable to task-specific cycles. The second group comprises the application of topology optimization method. Topology optimization approach is developed in the last decade and proved to be a promising approach for minimization of the mass of a structural member of machine component. Presented work will be helpful to understand the advancement in this domain.

Keyphrases: energy efficiency, lightweight design, Robotics, topology optimization, trajectory optimization

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:1540,
  author = {G Lakshmi Srinivas and Ruturaj Mane and Arshad Javed},
  title = {A Review on Optimization Methods to Enhance Energy Efficiency of Robots},
  howpublished = {EasyChair Preprint no. 1540},
  doi = {10.29007/djnw},
  year = {EasyChair, 2019}}
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