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JRM Vol.33 No.6 pp. 1248-1254
doi: 10.20965/jrm.2021.p1248
(2021)

Paper:

An Optimal Design Methodology for the Trajectory of Hydraulic Excavators Based on Genetic Algorithm

Takamichi Yuasa, Masato Ishikawa, and Satoshi Ogawa

Osaka University
2-1 Yamadaoka, Suita, Osaka 565-0871, Japan

Received:
July 5, 2021
Accepted:
October 11, 2021
Published:
December 20, 2021
Keywords:
hydraulic excavator, efficient excavation, nonlinear optimization, genetic algorithm
Abstract
An Optimal Design Methodology for the Trajectory of Hydraulic Excavators Based on Genetic Algorithm

Mathematical approach to trajectory design for hydraulic excavators

Hydraulic excavators are one type of construction equipment used in various construction sites worldwide, and their usage and scale are diverse. Generally, the work efficiency of a hydraulic excavator largely depends on human operation skills. If we can comprehend the experienced operation skills and utilize them for manual control assist, semi-automatic or automatic remote control, it would improve its work efficiency and suppress personnel costs, reduce the operator’s workload, and improve his/her safety. In this study, we propose a methodology to design efficient machine trajectories based on mathematical models and numerical optimization, focusing on ground-level excavation as a dominant task. First, we express its excavation trajectory using four parameters and assume the models for the amount of excavated soil and the reaction force based on our previous experiments. Next, we combine these models with a geometrical model for the hydraulic excavating machine. We then assign the amount of soil to a performance index preferably to be maximized and the amount of work to a cost index preferably to be minimized, both in the form of functions of the trajectory parameters, resulting in an optimization problem that trades them off. In particular, we formulate (1) a multi-objective optimization problem maximizing a weighted linear combination of the amount of soil and the amount of work as an objective function, and (2) a single-objective optimization problem maximizing the amount of soil under a given upper bound on the amount of work, so that we can solve these optimization problems using the genetic algorithm (GA). Finally, we conclude this paper by suggesting our notice on design methodology and discussing how we should provide the optimization method as mentioned above to the users who operate hydraulic excavators.

Cite this article as:
Takamichi Yuasa, Masato Ishikawa, and Satoshi Ogawa, “An Optimal Design Methodology for the Trajectory of Hydraulic Excavators Based on Genetic Algorithm,” J. Robot. Mechatron., Vol.33, No.6, pp. 1248-1254, 2021.
Data files:
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Last updated on Jan. 20, 2022