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Updated: Jul 2, 2025

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Operation of the Collaborative Composite Manufacturing CCM System
Published on: October 1, 2019
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不被调节和被调节的状态同时被限制最佳轨迹基于路径规划的控制对不被调节的机器人进行跟踪控制
IEEE transactions on cybernetics
|February 23, 2024
概括
这项研究引入了一种新的运动控制方法,用于未被调节的机器人,使得路径跟踪和约束满足既被调节和未被调节的状态. 该方法优化了时间轨迹,确保机器人安全高效地在复杂的环境中导航.
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
- 优化优化 优化优化
背景情况:
- 复杂环境中的未完成的机器人需要超越点对点方法的先进控制.
- 现有的路径规划方法往往会在不完善的系统中失败,或者依赖于简化的模型.
- 控制未加时状态,比如起重机的有效载荷摆动,存在重大挑战.
研究的目的:
- 开发一种用于一般低精度机器人的新型运动控制方法.
- 为了实现路径跟随和满足动作约束,无论是被激活的还是未激活的状态.
- 为了使缺乏直接控制输入的未完善系统能够进行时间最佳的轨迹规划.
主要方法:
- 提出了一种新的基于时间最佳轨迹规划的运动控制方法.
- 笛卡尔空间中的辅助信号用于表示联合空间变量.
- 位置/速度约束被转化为路径参数的优化不等式.
主要成果:
- 该方法成功地将全态约束转换为可解决的优化问题.
- 时间最佳轨迹是为动作状态推导的,确保路径遵循.
- 该方法实现了路径约束,时间优化和状态限制之间的平衡.
结论:
- 本文介绍了第一个方法,以确保在未达标系统中遵循路径和实现全状态约束.
- 拟议的框架通过在旋转起重机上进行分析和硬件实验来验证.
- 该方法提供了一个强大的解决方案,用于在复杂的场景中控制低精度的机器人.
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