Task-oriented optimal dimensional synthesis of robotic manipulators with limited mobility

Matteo Russo, Luca Raimondi, Xin Dong, Dragos Axinte, James Kell

Research output: Journal PublicationArticlepeer-review

11 Citations (Scopus)

Abstract

In this article, an optimization method is proposed for the dimensional synthesis of robotic manipulators with limited mobility, i.e. with less than 6 degrees-of-freedom (“DoF”), with a prescribed set of tasks in a constrained environment. Since these manipulators cannot achieve full 6-DoF mobility, they are able to follow only certain paths with prescribed position and orientation in space. While the most common approach to this problem employs pure path-planning algorithms, operations in narrow and complex environments might require changes to the robot design too. For this reason, this paper presents an improved approach which aims to minimize position and orientation error with a dimensional synthesis. First, a novel methodology that combines a path planning algorithm and dimensional synthesis has been proposed in order to optimize both robot geometry and pose for a given set of points. Then, the method is validated with a 4-DoF robot for high-precision laser operations in aeroengines as a case study. The example shows that the proposed procedure provides a stable algorithm with a high convergence rate and a short time to solution for robots with limited mobility in highly constrained scenarios.

Original languageEnglish
Article number102096
JournalRobotics and Computer-Integrated Manufacturing
Volume69
DOIs
Publication statusPublished - Jun 2021

Keywords

  • Dimensional Synthesis
  • Kinematics
  • Manipulators
  • Optimization

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Mathematics (all)
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

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