采矿绳的挖掘轨迹规划基于材料表面感知
Yinnan Feng1,2,3, Juan Wu1,2,3, Baoguo Lin1,2,3
1College of Mechanical and Vehicle Engineering, Taiyuan University of Technology, Taiyuan 030024, China.
Sensors (Basel, Switzerland)
|August 12, 2023
概括
本研究介绍了采矿绳 (MRS) 的智能轨迹规划方法,使用材料表面感知. 这种方法优化了开采,以提高开采采矿业的效率和节能.
科学领域:
- 机器人和自动化 机器人和自动化
- 地质技术工程 地质技术工程
- 机械工程 机械工程
背景情况:
- 露天采矿主要依赖于采矿绳 (MRS),这些正在过渡到智能无人操作.
- 有效的轨迹规划对于MRS的智能转型至关重要,要求考虑实时挖掘环境的方法.
研究的目的:
- 提出一种基于材料表面感知的MRS挖掘轨迹规划方法,用于智能采矿.
- 为MRS开发一种节能和节省时间的轨迹规划方法.
主要方法:
- 利用激光雷达获取点云数据,用于材料表面的重建和建模.
- 使用指数乘积 (PoE) 和拉格朗奇方程进行动力学和动力学分析.
- 采用第六阶多项式插值用于轨迹建模和灰狼优化器用于代优化.
主要成果:
- 提出的方法成功地规划了各种材料表面形状的轨迹.
- 实验验证证了计算模型的准确性,实际力量与计划力量保持一致.
- 该方法确保了全桶率和其他参数满足预定义的约束.
结论:
- 基于材料表面感知的轨迹规划方法在各种挖掘条件下对MRS是可行的.
- 这种方法有助于开采采矿操作的智能和无人转型.
- 开发的方法提高了挖掘效率和节能.
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