集体神经动力学用于冗余操纵器的稀疏运动规划,没有黑斯矩阵反转
IEEE transactions on neural networks and learning systems
|February 21, 2024
概括
这项研究引入了一种新的稀疏运动计划方案,用于冗余操纵器. 稀疏运动规划 (CNDSMP) 的集体神经动力学可以最大限度地减少过度的关节运动,提高工业机器人技术的效率并降低碰撞风险.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
- 控制系统 控制系统
背景情况:
- 冗余操纵器对于行业的效率和创新至关重要.
- 动力控制对于机器人轨迹跟踪至关重要.
- 现有的控制方案往往忽视了稀疏性,导致能源浪费和碰撞风险.
研究的目的:
- 为了解决冗余操纵器中过度关节运动的问题.
- 推出一种新的稀疏运动计划方案.
- 为了提高能源效率并降低碰撞概率.
主要方法:
- 制定稀疏性增强作为一个非凸的优化问题.
- 开发一个集体神经动力学稀疏运动规划 (CNDSMP) 计划.
- 通过模拟,比较和物理实验验证实方法.
主要成果:
- 拟议的CNDSMP计划有效地将过度的关节运动降到最低.
- 在能源效率方面取得了显著的改进.
- 降低了复杂环境中意外碰撞的风险.
结论:
- CNDSMP方案为冗余操纵器的运动控制提供了一个优质的解决方案.
- 整合稀疏性可以提高机器人系统的性能和安全性.
- 这些发现对先进的机器人和人工智能应用有影响.
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