Abstract

Appropriate reaction force design is essential to improve the lever operability of a hydraulic excavator that is difficult to operate. However, the force characteristics a human perceives when operating these levers are unknown. It is unclear whether the reaction force characteristics of the conventional lever are optimum for humans. Thus, this study aims to clarify the perceived force characteristics during the lever operation and verify the effectiveness of the lever reaction force design. In this study, a perceived force prediction method was proposed based on a musculoskeletal simulation for the lever operation. Also, it was confirmed that the perceived force could be estimated within a 7.8%–14.3% root mean square error. Furthermore, we developed the lever with the reaction force characteristics in which the perceived force varied linearly with the lever angle and confirmed that the proposed lever significantly improved operability when performing the leveling task with the excavator.

Highlights

  • The number of construction industry workers has been decreasing, and productivity improvement in the field has become a problem

  • We proposed a perceived force prediction method for the lever operation based on a musculoskeletal simulation

  • We proposed a method for predicting the perceived force during lever operation based on muscle activity estimation by a musculoskeletal simulation

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Summary

Introduction

The number of construction industry workers has been decreasing, and productivity improvement in the field has become a problem. Enhancing the work efficiency of a hydraulic excavator, which is a typical construction machine, is necessary to improve productivity. The operator needs advanced skills to efficiently operate the excavator. Sekizuka et al developed a system aimed to increase the efficiency of operational training for the excavator and constructed evaluation indices for the operation skills [1], [2]. This system enables training and is realized using a remote-controlled excavator and virtual reality technology

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