Open AccessOptimization approaches of industrial serial manipulators to improve energy efficiency: A review
Author(s) -
G. Lakshmi Srinivas,
Arshad Javed
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/912/3/032058
Subject(s) - robotics , robot , computer science , trajectory , field (mathematics) , topology optimization , industrial robot , mathematical optimization , point (geometry) , energy minimization , energy (signal processing) , trajectory optimization , efficient energy use , optimization problem , path (computing) , control engineering , artificial intelligence , engineering , optimal control , mathematics , algorithm , chemistry , structural engineering , geometry , programming language , statistics , physics , computational chemistry , astronomy , finite element method , pure mathematics , electrical engineering
The objective of this paper is to provide a comprehensive review of existing approaches and techniques developed in the field of industrial robotics to make it energy efficient. The usage of industrial manipulators is increasing globally due to its repeatability and superiority. The considerable energy demand is also predicted because of the increased application of robots in industries, this can be overcome by making energy-efficient manipulators. Different approaches are already established in this field to make robots energy efficient such as; elimination of needless densities by topology optimization, selection of optimal path using trajectory optimization, usage of light-weight components, analysing speed, and providing energy storage devices, etc. Among different available approaches, major three methodologies are reviewed in this paper. The first group comprises the topology optimization method that optimizes the design space by eliminating needless densities based on given boundary conditions and constraints. Further, the topology optimization method sub-classified into two types based on loading conditions such as static analysis and dynamic analysis. The second group comprises trajectory optimization of robots; this is achieved by selecting the optimal path of the work-cycle, or minimization of torque. Again trajectory optimization classified into point-to-point and multi-point optimization. The third group includes the application of light-weight structural components in the field of industrial robotics and its challenges. Presented work will be useful to analyze different approaches to make the robot as energy efficient.