实现高度冗余的移动操纵器协调规划和层次优化控制
Erdi Sayar1, Xiang Gao1, Yingbai Hu2
1School of Computation, Information and Technology, Technical University of Munich, Munich, 85748, Germany.
ISA transactions
|January 16, 2024
概括
这项研究引入了复杂的室内环境中移动操纵器的新型控制方案. 它通过结合无限规范和松变量来增强优化,以改善关节限制处理和约束放松,从而实现更有效的机器人控制.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 控制系统 控制系统
- 人工智能的人工智能
背景情况:
- 移动操纵器需要复杂的室内环境的先进控制.
- 传统的优化方法在冗余系统中与联合限制和约束作斗争.
研究的目的:
- 为高度冗余的移动操纵器开发一个约束规划和优化控制方案.
- 改进操纵器控制中的联合限制和平等约束的处理.
- 在复杂的室内环境中实现有效的路径规划和跟踪控制.
主要方法:
- 在优化算法中引入了无限度规范和松变量.
- 使用衍生动力学方程,将跟踪控制问题表达为二次编程 (QP) 问题.
- 提出了一个两次级的循环神经网络优化方案.
- 集成了BI2RRT*路径规划算法,用于复杂的环境.
主要成果:
- 在基于9个自由度 (DOFs) 的非holonomic移动操纵器上成功测试了优化方案.
- 在模拟复杂的室内环境中证明有效的路径规划和跟踪控制.
- 在神经机器人平台 (NRP) 中使用预定义和生成的路径验证了方法.
结论:
- 拟议的约束规划和优化控制方案有效地管理了共同的限制和约束.
- 两个时间尺度的循环神经网络优化方案为移动操纵器控制提供了强大的解决方案.
- 该BI2RRT*算法增强了混乱的室内空间的路径规划能力.
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