论文《面向自主作业的挖掘机多目标最优挖掘运动规划》数据集

对反铲挖掘机进行运动规划是实现自主作业前提。以最短挖掘时间和最低挖掘能耗为目标，本文提出了一种挖掘运动规划的方法。以 21 吨级反铲液压挖掘机为研究对象，首先结合采集的挖掘作业载荷谱和对应的斗尖轨迹，在保证满斗率大于 0.9 前提下，提取一条单位质量能耗最小的挖掘轨迹作为目标轨迹进行最优运动规划。进一步建立了挖掘机工作装置动力学模型，并通过实测数据验证了该动力学模型的准确性。在此基础上建立以斗尖初速度和加速度为优化变量，以最短挖掘时间和最低挖掘能耗为目标的优化模型。引入权重系数表征不同的挖掘作业模式后，利用遗传算法对优化模型进行优化求解。

Motion planning for backhoe excavators is the prerequisite for achieving autonomous operations. Aiming to minimize both excavation time and energy consumption, this paper proposes an excavation motion planning method. Taking a 21-ton class backhoe hydraulic excavator as the research subject, this study first combines the collected excavation operation load spectrum and the corresponding bucket tip trajectory, extracts an excavation trajectory with the minimum energy consumption per unit mass as the target trajectory for optimal motion planning under the premise of ensuring that the bucket fill rate is greater than 0.9. Furthermore, a dynamic model of the excavator's working device is established, and the accuracy of this dynamic model is verified using measured data. On this basis, an optimization model is constructed, which takes the initial velocity and acceleration of the bucket tip as the optimization variables, and takes the shortest excavation time and the lowest excavation energy consumption as the optimization objectives. After introducing weight coefficients to characterize different excavation operation modes, the genetic algorithm is employed to optimize and solve the established optimization model.

搜集汇总

背景与挑战

背景概述

该数据集围绕挖掘机自主作业的运动规划问题，提供了以21吨级反铲液压挖掘机为研究对象的实验数据，包括挖掘作业载荷谱、斗尖轨迹等，旨在通过遗传算法优化实现最短挖掘时间和最低能耗的多目标规划。数据集包含数据说明文件、Excel表格和PDF论文，总大小9.75MB，来源于国家重点研发计划项目，适用于流体传动与控制领域的研究和应用。