Development of an environment characterization methodology for optimal design of an agricultural robot

Victor Bloch, Avital Bechar, Amir Degani

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Purpose - The purpose of this paper is to describe a methodology for characterization of the robot environment to help solve such problem as designing an optimal agricultural robot for a specific agricultural task. Design/methodology/approach - Defining and characterizing a task is a crucial step in the optimization of a task-specific robot. It is especially difficult in the agricultural domain because of the complexity and unstructured nature of the environment. In this research, trees are modeled from orchards and are used as the robot working environment, the geometrical features of an agricultural task are investigated and a method for designing an optimal agricultural robot is developed. Using this method, a simplified characteristic environment, representing the actual environment, is developed and used. Findings - Case studies showing that the optimal robot, which is designed based on the characteristic environment, is similar to the optimal robot, which is designed based on the actual environment (less than 4 per cent error), is presented, while the optimization run time is significantly shorter (up to 22 times) when using the characteristic environment. Originality/value - This paper proposes a new concept for solving the robot task-based optimization by the analysis of the task environment and characterizing it by a simpler artificial task environment. The methodology decreases the time of the optimal robot design, allowing to take into account more details in an acceptable time.

Original languageEnglish
Pages (from-to)94-103
Number of pages10
JournalIndustrial Robot
Volume44
Issue number1
DOIs
StatePublished - 1 Jan 2017
Externally publishedYes

Keywords

  • Agriculture
  • Field robotics
  • Robot design
  • Robot task characterization

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

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