基于3D视觉的清洁机器人的运动计划
Lifeng Wang1,2, Wenming Cheng1, Chaoze Wang3
1Southwest Jiao Tong University, Chengdu, China.
Science progress
|November 24, 2025
概括
本研究介绍了一个用于工业清洁的3D视觉机器人,提高效率和减少浪费. 它使用先进的AI进行精确的清洁和路径优化,提高工件清洁质量.
科学领域:
- 机器人和自动化 机器人和自动化
- 计算机视觉 计算机视觉
- 工业工程 工业工程 工业工程
背景情况:
- 传统的工业清洁面临着水浪费,盲点和设备兼容性差等挑战.
- 现有的方法往往缺乏适应不同材料和染色类型的适应性.
- 需要自动化清洁解决方案来提高制造业的效率和质量.
研究的目的:
- 开发一个基于3D视觉的清洁机器人,用于工业应用,特别是铁路运输设备制造.
- 通过集成智能控制和先进的识别算法来解决当前清洁方法的局限性.
- 提高清洁效率,质量和资源管理 (例如,用水量).
主要方法:
- 一个与清洁机器人集成的三维视觉系统.
- 比例整数导数 (PID) 控制器用于精确调节清洗压力和水温.
- 改进了CIoU-YOLOv7对象识别和模板匹配,用于工件和污点识别.
- 清洗路径优化的遗传算法.
主要成果:
- 实现了62.34%的工件识别精度,比基线算法提高了5-10%.
- 与基本遗传算法相比,优化清洁路径减少了总路径长度64.7%,效率提高了10.5%.
- 将最佳解决方案的代数减少了95%,这表明智能和效率得到了提高.
结论:
- 拟议的基于3D视觉的清洁机器人有效地解决了工业清洁的局限性,包括水浪费和低效率.
- 集成先进的算法增强了工件识别,定位和清洁路径优化.
- 该系统为制造应用提供了清洁效率,质量和资源节约方面的显著改进.
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