离散时间视觉伺服控制与基于操纵器动态的自适应图像特征预测.
Chenlu Liu1, Chao Ye1, Hongzhe Shi1
1Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin 150001, China.
Sensors (Basel, Switzerland)
|July 27, 2024
概括
本研究介绍了一种基于图像的视觉伺服 (IBVS) 的自适应控制方法,该方法可以预测图像特征以改善机器人控制. 该技术增强了系统的稳定性,并加速了机器人手臂的融合.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 计算机视觉 计算机视觉
- 控制系统 控制系统
背景情况:
- 基于图像的视觉伺服 (IBVS) 系统面临的挑战是离散时间控制循环的时间延迟.
- 精确估计图像特征和流的机器人速度控制对于IBVS性能至关重要.
研究的目的:
- 开发一种实用的离散时间控制方法,用于IBVS与自适应图像特征预测.
- 为了解决时间延迟,并改善机器人操纵器控制的动态特性.
主要方法:
- 提出了一种线性动态模型来描述6DOF (自由度) 操纵器端效应器的运动.
- 使用历史图像特征和机器人速度数据开发了一种自适应图像特征预测方法.
主要成果:
- 拟议的方法有效地估计图像特征,并平滑机器人速度输入.
- 在6DOF机器人臂上的实验结果证实了增强的系统稳定性和更快的融合.
结论:
- 适应性图像特征预测方法提高了离散时间IBVS的性能.
- 这种方法确保了系统的稳定性,并加速了机器人操纵器控制的融合.
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