基于BFS-canny图像边缘检测算法的机器人臂视觉伺服系统的性能分析.
Yuling Yan1,2, Siti Salasiah Mokri3
1Faculty of Engineering and Built Environment (FKAB), Universiti Kebangsaan Malaysia (UKM), Bangi Selangor, 43600, Malaysia.
Scientific reports
|October 9, 2025
概括
本研究引入了用于机器人臂视觉伺服的高级图像边缘检测算法,显著提高了实时性能和稳定性. 这种新方法可以提高机器人手臂在复杂环境中的智能和感知.
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
- 图像处理 图像处理
背景情况:
- 视觉伺服通过视觉反增强机器人手臂的智能.
- 目前视觉服务中的图像处理面临实时性能和稳定性挑战.
研究的目的:
- 为机器人臂视觉服务开发一个高效的图像边缘检测算法.
- 为了提高机器人手臂系统的实时性能,稳定性和可靠性.
主要方法:
- 结合宽度第一搜索,Cannie和哈里斯算法与并行处理.
- 开发了一种新的图像边缘检测算法.
- 建立了一个机器人臂视觉伺服系统,结合了算法.
主要成果:
- 拟议的算法在增加数据量时,与现有方法相比,表现出更高的性能.
- 获得的准确性,回忆力和F1分数分别超过95%,86%和90%.
- 在4096*2160图像中达到110FPS的计算效率,并保持至少30.28ms的平均运行时间.
结论:
- 开发的算法有效地提高了机器人臂视觉伺服系统的性能和可靠性.
- 该方法提高了动态跟踪性能,并使复杂环境中的感知成为可能.
- 这项研究有助于推进智能机器人手臂应用.
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