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Digging Trajectory Optimization by Soil Models and Dynamics Models of Excavator

Journal Article
2013-01-2411
ISSN: 1946-391X, e-ISSN: 1946-3928
Published September 24, 2013 by SAE International in United States
Digging Trajectory Optimization by Soil Models and Dynamics Models of Excavator
Sector:
Citation: Yoshida, T., Koizumi, T., Tsujiuchi, N., Jiang, Z. et al., "Digging Trajectory Optimization by Soil Models and Dynamics Models of Excavator," SAE Int. J. Commer. Veh. 6(2):429-440, 2013, https://doi.org/10.4271/2013-01-2411.
Language: English

Abstract:

Researches for automated construction machinery have been conducted for labor-saving, improved work efficiency and worker's safety, where a tracking control function was proposed as one of the key control system strategies for highly automated productive hydraulic excavators. An optimized digging trajectory that assures as much soils scooped as possible and less energy consumption is critical for an automated hydraulic excavator to improve work efficiency.
Simulation models that we used to seek an optimized digging trajectory in this study consist of soil models and front linkage models of a hydraulic excavator. We developed two types of soil models. One is called wedge models used to calculate reaction forces from soils acting on a bucket during digging operation, based on the earth pressure theory. The other is called Distinct Element Method (DEM) model used to analyze soil behaviors and estimate amounts of soils scooped and reaction forces quantitatively. In this simulation, we calculated generative forces and energy consumptions of hydraulic cylinders by solving inverse dynamics of the linkages.
Firstly, we used wedge models that enable extremely high-speed calculations, to look for numerous combinations of trajectory parameters and select ones with less energy consumption. Then, we used DEM models that enable detailed analysis by combining with the front linkage models to evaluate digging efficiencies of the selected trajectories. The results show that the trajectories with the highest efficiency generated in this research exceeds the efficiency level of a skilled operator by 6.6%.