Development of an environment characterization methodology for optimal design of an agricultural robot. Issue 1 (16th January 2017)

• Record Type: Journal Article
• Authors: Bloch, Victor; Bechar, Avital; Degani, Amir
• Is Part Of: Industrial robot. Volume 44:Issue 1(2017)
• Page Start: 94
• Page End: 103
• Publication Date: 2017-01-16
• Subjects: Agriculture -- Robot design -- Field robotics -- Robot task characterization; Robots, Industrial -- Periodicals; Machinery in the workplace -- Periodicals; 629.892
• DOI: 10.1108/IR-03-2016-0113
• Languages: English
• ISSNs: 0143-991X

Abstract

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.