在对接时控制AGV基于模糊规则推理系统
Damian Grzechca1, Łukasz Gola1, Michał Grzebinoga1
1Department of Electronics, Electrical Engineering and Microelectronics, Silesian University of Technology, 44-100 Gliwice, Poland.
Sensors (Basel, Switzerland)
|October 16, 2025
概括
本研究提出了一种纯软件解决方案,以提高自动驾驶汽车 (AGV) 的对接精度. 一个新的模糊逻辑控制器提高了工业4.0自动化的精度,而不需要新的硬件.
科学领域:
- 机器人和自动化 机器人和自动化
- 控制系统工程 控制系统工程
- 工业信息学 工业信息学
背景情况:
- 自动引导车辆 (AGV) 的准确对接对于工业4.0自动化生产系统至关重要.
- 使用机器人臂的协作任务需要高的AGV定位精度.
- 传统的测距系统存在累积错误,在最后的对接过程中变得不可接受.
研究的目的:
- 引入一个具有成本效益的软件升级解决方案,以提高AGV对接精度.
- 为了提高最终对接阶段的准确性,而不需要新的硬件.
- 在关键对接场景中解决全球导航和测距的局限性.
主要方法:
- 一个两阶段的导航策略:从全球死亡计算转向靠近对接站的本地计划.
- 实现一个塔卡吉-苏杰诺模糊逻辑控制器 (FLC) 精确的最终定位.
- 在FLC中使用增益调度查找表 (LUT) 来从近距离传感器数据中合成方向和距离错误.
主要成果:
- 模糊逻辑控制器成功地引导AGV以高精度到达最终位置.
- 基于LUT的FLC可稳定处理位置不确定性和环境变化.
- 实验验证表明,在工业宽容范围内,可重复对接的准确性得到了显著改善.
结论:
- 提出的软件升级解决方案有效地提高了AGV对接精度.
- 新的FLC方法为改进自动化生产系统提供了一种具有成本效益的方法.
- 这种方法克服了对关键对接任务的传统测距的局限性.
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